CN116308970A - Rail site service range analysis method based on travel chain generalized travel expense - Google Patents

Rail site service range analysis method based on travel chain generalized travel expense Download PDF

Info

Publication number
CN116308970A
CN116308970A CN202310129305.1A CN202310129305A CN116308970A CN 116308970 A CN116308970 A CN 116308970A CN 202310129305 A CN202310129305 A CN 202310129305A CN 116308970 A CN116308970 A CN 116308970A
Authority
CN
China
Prior art keywords
travel
rail
expense
generalized
service range
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310129305.1A
Other languages
Chinese (zh)
Inventor
李文勇
宋艺欣
廉冠
王涛
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guilin University of Electronic Technology
Original Assignee
Guilin University of Electronic Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guilin University of Electronic Technology filed Critical Guilin University of Electronic Technology
Priority to CN202310129305.1A priority Critical patent/CN116308970A/en
Publication of CN116308970A publication Critical patent/CN116308970A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0283—Price estimation or determination
    • G06Q30/0284—Time or distance, e.g. usage of parking meters or taximeters

Landscapes

  • Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Development Economics (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Game Theory and Decision Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Primary Health Care (AREA)
  • Tourism & Hospitality (AREA)
  • Train Traffic Observation, Control, And Security (AREA)

Abstract

The invention relates to the technical field of rail transit analysis, in particular to a rail station service range analysis method based on travel chain generalized travel expense.

Description

Rail site service range analysis method based on travel chain generalized travel expense
Technical Field
The invention relates to the technical field of rail transit analysis, in particular to a rail station service range analysis method based on travel chain generalized travel expense.
Background
The rail station service range refers to a station passenger flow generation area, and comprises a passenger flow suction area, a passenger flow radiation area, a passenger flow connection area and the like. The travel chain is a link form formed by a plurality of continuous travel in a certain time sequence for indicating the traveler to complete a plurality of purposes. The track traffic travel chain is a multi-mode combined travel taking track traffic as a main body. Because the gathering and evacuation of the rail transit passenger flows can only be completed through the stations, the rail stations directly determine the attractive force of the rail transit mode on the passenger flows in other modes, and determine the service level of the rail transit. To fully exert the service function of urban rail transit and improve the attractiveness of the urban rail transit in the urban transportation travel mode, the service range of the rail station needs to be clearly identified and analyzed.
The existing track site service range determining method is mainly defined by subjective experience through a distance threshold of 400-1000 m in a unified mode, and large deviation exists. Thus, researchers have developed detailed studies of the site service area. One is based on the analysis method of the data, consider the impact factors such as going out environment, trip purpose, etc., establish the Logit model through resident going out survey, confirm the range of connection of the orbit website; the other is an analysis method based on a model, and a track site reachability model based on a radiation range is established by taking the built environment and travel cost around the track site into consideration.
However, in the prior art, it was found that passengers choose to transfer the rail traffic by a certain connection mode, and this is usually because the exit point of the rail traffic is closer to the destination, which means that when selecting the rail traffic, the traveler considers not only the access terminal but also the generalized travel cost in the whole travel process.
Disclosure of Invention
The invention aims to provide a rail station service range analysis method based on travel chain generalized travel expense, which is used for analyzing the rail station service range through a generalized travel expense minimum model under the condition that passengers consider that the generalized travel expense of the whole travel process is minimum, so that the attractiveness of rail traffic is improved.
In order to achieve the above purpose, the invention provides a rail station service range analysis method based on travel chain generalized travel expense, which comprises the following steps:
step 1: using POI searching function, selecting multiple departure places around the track site by taking the track site as the circle center;
step 2: selecting a destination through passenger flow data;
step 3: selecting a departure place and a destination to form an OD pair, and enumerating possible path schemes under each OD pair by using a path planning function of a map;
step 4: substituting the corresponding path scheme into a travel chain generalized travel expense model for comparison and selection,
if the route is a travel chain taking rail traffic as a main body, the rail traffic station is a circle center station in the steps, but not other stations, the generalized travel cost of the rail traffic travel chain in all possible routes is minimum, and the departure place meeting the condition is brought into the station service range;
and eliminating the departure place which does not meet the condition.
The POI searching function adopts a peripheral searching POI function in the Goldmap API interface.
The method comprises the steps of selecting a plurality of departure places around a track site by taking the track site as a circle center, defining a searching radius of 800m by taking the track site as the circle center, searching all residential communities around the track site, and selecting the plurality of residential communities as the departure places around the track site.
The destination of the traveler cannot be determined, the main passenger flow distribution points of the city are used as destination objects, and a business district or public place with larger passenger flow is selected as the destination according to subway passenger flow data.
Wherein the mode combination of each OD versus the next possible path scheme mainly covers the following seven types:
walking + rail + walking;
riding+rail+walking;
walking + rail + riding;
riding+track+riding;
bus+rail+walk;
walking + rail + bus;
bus+track+bus.
The travel chain generalized travel expense comprises time expense, riding expense and comfort degree expense, wherein the time expense refers to the total time spent by passengers from a travel starting point to a travel ending point, and is equivalent converted into a corresponding expense form according to time value; the riding expense is the riding expense generated by passengers using the vehicles; the comfort cost is quantified by the product of the fatigue penalty coefficient and the time and travel time value.
The fatigue penalty coefficients comprise a sports fatigue penalty coefficient and a psychological fatigue penalty, wherein the sports fatigue penalty coefficient increases along with the increase of the travel distance and is applicable to travel modes which can cause obvious sports fatigue; the psychological fatigue penalty coefficient increases along with the increase of travel time, and is suitable for travel modes without obvious exercise type fatigue.
The invention provides a rail station service range analysis method based on travel chain generalized travel expense, which utilizes path planning in a Gaode API interface to determine various parameters in travel paths and generalized travel expense, determines the service range of a rail traffic station from the consideration of travel chain angles, and meanwhile, based on a service range analysis model of the travel chain generalized travel expense, compared with the existing rail traffic station service range analysis method, the service range of the rail station is considered from the minimum travel chain generalized travel expense, and the important factors considered by a traveler, namely comfort expense, are referenced in the traditional generalized expense for modeling, so that the travel requirement of the traveler at present is more met, the service range is divided more finely, and the attraction of rail traffic is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow diagram of a track site service range analysis method based on travel chain generalized travel expense.
Fig. 2 is a schematic diagram of a possible path example of the track traffic travel chain of the present invention.
Fig. 3 is a schematic diagram of a site service scope analysis flow of the present invention.
Fig. 4 is an exemplary schematic diagram of a possible path travel chain scheme of the foreign dominant life time-the morning sun square in the specific embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
Referring to fig. 1, the invention provides a rail site service range analysis method based on travel chain generalized travel expense, which comprises the following steps:
s1: using POI searching function, selecting multiple departure places around the track site by taking the track site as the circle center;
s2: selecting a destination through passenger flow data;
s3: selecting a departure place and a destination to form an OD pair, and enumerating possible path schemes under each OD pair by using a path planning function of a map;
s4: substituting the corresponding path scheme into a travel chain generalized travel expense model for comparison and selection,
if the route is a travel chain taking rail traffic as a main body, the rail traffic station is a circle center station in the steps, but not other stations, the generalized travel cost of the rail traffic travel chain in all possible routes is minimum, and the departure place meeting the condition is brought into the station service range;
and eliminating the departure place which does not meet the condition.
In step S1, a POI search function in the german map API interface is adopted, and a 800m radius search range is set with the track site as the center of a circle, so as to search all residential cells around the track site as the departure place around the site.
In step S2, since the destination of the traveler cannot be specified, a main traffic distribution point of the city is used as a destination object, and a business district or public place with a large traffic is selected as a destination according to subway traffic data.
In step S3, each departure point O, namely, a cell POI, and each destination point D are made into OD pairs, and a possible path under each OD pair is determined by using a "path planning" function, wherein the possible paths of the track traffic travel chain are shown in fig. 2, and triangles in the figure represent passenger flow suction points, namely, departure points and destinations, circles represent subway station entrances and exits, squares represent the riding and descending points of tracks, buses and shared buses; the dashed arrows represent walking sections, the stippled arrows represent getting on and off sections, and the straight arrows represent riding sections. Specifically, seven possible combinations of modes are included:
(1) Walking + rail + walking;
(2) Riding+rail+walking;
(3) Walking + rail + riding;
(4) Riding+track+riding;
(5) Bus+rail+walk;
(6) Walking + rail + bus;
(7) Bus+track+bus.
In step S4, the travel chain generalized travel costs mainly include time costs, riding costs, and comfort costs.
The time cost refers to the total time spent by passengers from the trip starting point to the trip ending point, and the time cost is equivalent converted into a corresponding cost form according to the time value. The total time of the whole travel process mainly comprises waiting time, riding time, searching time, traffic control, station stop time delay and the like. Travel time Value (VOT) is quantified as a time fee. In the traffic field, the time value of the traveler is put forward on the basis of saving time and reasonably utilizing, namely, the ratio of the average income of the traveler to the average working time reflects the opportunity cost of the time spent on the traveling relative to the traveler. Therefore, the travel time value is determined according to the income method, and the calculation formula is as follows:
Figure BDA0004083225990000051
wherein VOT is travel time value, meta/min; INC is the average monthly revenue (yuan) for the traveler; t is the average working time (min) of the traveler.
For example, in the present invention, it is known that the average value of the average monthly income of the residents in the year 2021 in the Nanning city is 4973 yuan, and the average wages in the year Nanning city is 28.1 yuan as calculated by working 22d per month and 8 hours per day, and the value is set to 0.468 yuan/min as the travel time value of the residents in the present invention.
The riding expense is mainly riding expense generated by a vehicle when a passenger selects a certain vehicle. The invention uses the concept of the freight rate to represent the actual travel cost of a certain traffic mode in unit distance.
The comfort cost is quantitatively represented by the travel fatigue degree, and the greater the fatigue degree is, the lower the travel comfort degree is. According to the invention, fatigue penalty coefficients are introduced, and the fatigue penalty coefficients are divided into two types according to different fatigue generated by different travel modes: firstly, the exercise type fatigue penalty coefficient increases along with the increase of the travel distance, namely, the travel modes such as walking, riding and the like can cause obvious exercise type fatigue; and secondly, the psychological fatigue penalty coefficient is increased along with the increase of travel time, namely, the travel mode without obvious movement type fatigue such as conventional buses, rail transit and the like.
Further, the rail site service range analysis model based on the travel chain generalized travel expense comprises the following parts:
the objective function for determining the service scope boundary is:
Figure BDA0004083225990000052
the constraint conditions are as follows:
Figure BDA0004083225990000053
Figure BDA0004083225990000061
x iu ＝{0,1},i∈M,u∈P (4)
the generalized cost of each travel stage in a single travel chain is as follows:
Figure BDA0004083225990000062
Figure BDA0004083225990000063
Figure BDA0004083225990000064
in the method, in the process of the invention,
Figure BDA0004083225990000065
in the process from the departure place i to the destination j, the vehicle travels by rail transit, and the two ends of the rail transit uv station adopt generalized travel cost of the transportation mode z connection;
m, N, P, Q are respectively a set of departure place traffic cells, a set of destination traffic cells, a set of rail transit inbound stations and a set of rail transit outbound stations;
Figure BDA0004083225990000066
C u-v ，/>
Figure BDA0004083225990000067
the generalized travel cost of each stage on the travel chain is respectively represented, namely, the generalized travel cost from the departure place i to the rail station u in a traffic mode z, the generalized travel cost from the rail station u to the rail station v, and the generalized travel cost from the rail station v to the destination j in the traffic mode z;
x iu -0, 1 variable, x when traffic cell i is attracted by rail site u iu =1; otherwise x iu ＝0；
z-one of travel, walking, riding, public transportation, and track;
l iu ，l uv ，l vj -distance of each travel phase in the travel chain;
Figure BDA00040832259900000614
uv ，/>
Figure BDA0004083225990000069
-travel time of the traffic means z is adopted for each travel phase in the travel chain;
Figure BDA00040832259900000610
the searching time of the traffic mode z mainly refers to the searching time of a shared bicycle and other time consumption of positioning the bicycle, unlocking and the like by using a smart phone;
Figure BDA00040832259900000611
-waiting time for taking a bus or subway;
Figure BDA00040832259900000612
-delay time of traffic means, including traffic control and time delay of stop of the station;
r z -the rate of freight rate for transportation means z;
μ z -fatigue penalty coefficient of traffic pattern z, and
Figure BDA00040832259900000613
vot-travel time value, travel cost per unit travel time.
The formula (1) is an objective function, and represents that n traffic cells are allocated to m track stations, and the generalized travel cost from a destination is considered to be minimum when the track stations are selected, so that the total cost of a travel chain mainly comprising the track traffic is minimum; equation (2) is a calculation formula of generalized travel expense, and is determined by travel distance, travel time and travel comfort; equation (3) ensures that each traffic cell i is served by and by only one rail site; equation (4) is an integer constraint of the model. By using the model, nearest distribution based on minimum comprehensive destination cost can be performed, and a possible passenger flow source area of the subway station, namely a service range boundary, is obtained.
The invention also provides a specific embodiment for verification and auxiliary description:
the specific flow of the service range analysis method is shown in fig. 3, the embodiment specifically uses the district around the south-to-north Hunan road station in the nan ning city as the departure place, uses the main business district center in the nan ning city, namely the morning sun square as the destination, adopts the Goldmap path planning, the (departure place-destination) OD path scheme example is shown in fig. 4 in detail, each actual numerical value of the path scheme obtained by the Goldmap path planning tool is brought into the model, and the generalized travel cost of the travel chain is calculated, wherein the list is as follows:
TABLE 1OD trip chain possible Path generalized trip cost example
Figure BDA0004083225990000071
As shown in table 1, the generalized travel cost of the rail transit travel chain is the smallest in the three travel chains of the overseas excellent living age-the morning square, the south ning university (the Ming Xiujun district) -the morning square, the chang tai zuno house-the morning square, so that all the three departure places can be brought into the rail station service range, and the generalized travel cost of the public transit travel chain of the baoding-the morning square is higher than that of the rail travel chain, so that the point is not brought into the rail station service range.
The above disclosure is only a preferred embodiment of the present invention, and it should be understood that the scope of the invention is not limited thereto, and those skilled in the art will appreciate that all or part of the procedures described above can be performed according to the equivalent changes of the claims, and still fall within the scope of the present invention.

Claims (7)

1. The rail site service range analysis method based on the travel chain generalized travel expense is characterized by comprising the following steps of:
step 1: using POI searching function, selecting multiple departure places around the track site by taking the track site as the circle center;
step 2: selecting a destination through passenger flow data;
step 3: selecting a departure place and a destination to form an OD pair, and enumerating possible path schemes under each OD pair by using a path planning function of a map;
step 4: substituting the corresponding path scheme into a travel chain generalized travel expense model for comparison and selection,
if the route is a travel chain taking rail traffic as a main body, the rail traffic station is a circle center station in the steps, but not other stations, the generalized travel cost of the rail traffic travel chain in all possible routes is minimum, and the departure place meeting the condition is brought into the station service range;
and eliminating the departure place which does not meet the condition.
2. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 1, wherein,
the POI search function adopts a peripheral search POI function in the Goldmap API interface.
3. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 2, wherein,
the method comprises the steps of selecting a plurality of departure places around a track site by taking the track site as a circle center, defining a searching radius of 800m by taking the track site as the circle center, searching all residential communities around the track site, and selecting the plurality of residential communities as the departure places around the track site.
4. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 3,
since the destination of the traveler cannot be determined, the main passenger flow collection and distribution points of the city are used as destination objects, and a business district or public place with larger passenger flow is selected as the destination according to subway passenger flow data.
5. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 4, wherein,
the combination of ways of the possible path schemes under each OD pair covers mainly the following seven:
walking + rail + walking;
riding+rail+walking;
walking + rail + riding;
riding+track+riding;
bus+rail+walk;
walking + rail + bus;
bus+track+bus.
6. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 5, wherein,
the generalized travel expense of the travel chain comprises time expense, riding expense and comfort expense, wherein the time expense refers to the total time spent by passengers from a travel starting point to a travel ending point, and is equivalent converted into a corresponding expense form according to time value; the riding expense is the riding expense generated by passengers using the vehicles; the comfort cost is quantified by the product of the fatigue penalty coefficient and the time and travel time value.
7. The method for analyzing the service range of the rail site based on the generalized travel expense of the travel chain according to claim 6, wherein,
the fatigue penalty coefficients comprise a sports fatigue penalty coefficient and a psychological fatigue penalty, and the sports fatigue penalty coefficient is increased along with the increase of the travel distance and is applicable to travel modes which can cause obvious sports fatigue; the psychological fatigue penalty coefficient increases along with the increase of travel time, and is suitable for travel modes without obvious exercise type fatigue.
CN202310129305.1A 2023-02-17 2023-02-17 Rail site service range analysis method based on travel chain generalized travel expense Pending CN116308970A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310129305.1A CN116308970A (en) 2023-02-17 2023-02-17 Rail site service range analysis method based on travel chain generalized travel expense

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310129305.1A CN116308970A (en) 2023-02-17 2023-02-17 Rail site service range analysis method based on travel chain generalized travel expense

Publications (1)

Publication Number Publication Date
CN116308970A true CN116308970A (en) 2023-06-23

Family

ID=86796998

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310129305.1A Pending CN116308970A (en) 2023-02-17 2023-02-17 Rail site service range analysis method based on travel chain generalized travel expense

Country Status (1)

Country Link
CN (1) CN116308970A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117540933A (en) * 2024-01-04 2024-02-09 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117540933A (en) * 2024-01-04 2024-02-09 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction
CN117540933B (en) * 2024-01-04 2024-04-05 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction

Similar Documents

Publication Publication Date Title
Rastogi et al. Travel characteristics of commuters accessing transit: Case study
CN110704993B (en) Customized bus route design method for relieving subway passenger flow pressure
CN103714257B (en) A kind of public transport problem identification of lines technology
CN106960406A (en) A kind of bus service coverage rate computational methods for considering resident trip OD
CN109729518B (en) Mobile phone signaling-based urban traffic early peak congestion source identification method
CN112784000B (en) Passenger searching method based on taxi track data
Gendreau et al. Locating rapid transit lines
CN116308970A (en) Rail site service range analysis method based on travel chain generalized travel expense
CN112184281A (en) Railway junction passenger demand prediction method based on travel space classification
Lowson New approach to effective and sustainable urban transport
CN113538886A (en) Real-time response type customized bus hierarchical scheduling method
CN114511143A (en) Urban rail transit network generation method based on grouping division
CN111341135A (en) Mobile phone signaling data travel mode identification method based on interest points and navigation data
CN113408833A (en) Public traffic key area identification method and device and electronic equipment
Jaiswal et al. Optimization of public transport demand: a case study of Bhopal
CN113053156B (en) Intelligent bus station addressing method based on bus radius method
CN111931386B (en) Method and system for calculating congestion coefficient of regional multi-standard rail traffic interval
Chaberek-Karwacka Organizational and infrastructural solutions in creating competitive advantage of sustainable urban transport-Gdańsk case study
CN115127569A (en) Personalized intermodal navigation method and system
Putri et al. Study of Public Transport Development in South Bali Districts: Potential Public Transport Mode
Araldo et al. Pooling for first and last mile: Integrating carpooling and transit
CN111859717A (en) Method and system for minimizing regional multi-standard rail transit passenger congestion coefficient
Luoma et al. The future of personal transportation in megacities of the world
Hsu et al. A model on market share distribution between air transportation, high-speed rail, and automobiles
KR102433434B1 (en) Assumption system for alighting information of the public transportation and thereof

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination