CN112365042A - Trip passenger service evaluation method and device based on trip chain - Google Patents
Trip passenger service evaluation method and device based on trip chain Download PDFInfo
- Publication number
- CN112365042A CN112365042A CN202011230484.0A CN202011230484A CN112365042A CN 112365042 A CN112365042 A CN 112365042A CN 202011230484 A CN202011230484 A CN 202011230484A CN 112365042 A CN112365042 A CN 112365042A
- Authority
- CN
- China
- Prior art keywords
- travel
- preset position
- preset
- path
- calculating
- 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
Links
- 238000011156 evaluation Methods 0.000 title claims description 155
- 238000000034 method Methods 0.000 claims abstract description 40
- 238000012546 transfer Methods 0.000 claims description 77
- 230000002087 whitening effect Effects 0.000 claims description 22
- 230000006870 function Effects 0.000 claims description 18
- 230000015654 memory Effects 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 13
- 238000003860 storage Methods 0.000 claims description 11
- 239000011159 matrix material Substances 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 abstract description 18
- 238000005457 optimization Methods 0.000 abstract description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 6
- 238000011161 development Methods 0.000 description 5
- 238000012163 sequencing technique Methods 0.000 description 4
- 238000011160 research Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000010006 flight Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000013441 quality evaluation Methods 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000012351 Integrated analysis Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004132 cross linking Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005304 joining Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000029305 taxis Effects 0.000 description 1
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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a trip chain-based joint passenger service assessment method and device, wherein the method comprises the following steps: acquiring first travel data of a plurality of travel paths between a first preset position and a second preset position; calculating path characteristics between a first preset position and a second preset position according to the first travel data of each travel path; and calculating and analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position. When the comprehensive transportation passenger service quality is analyzed by implementing the method, the analysis result is more comprehensive by combining the plurality of path characteristics of the first travel data, and the comprehensive transportation passenger service quality of the travel path between two specific positions can be obtained by implementing the method, so that the analysis result is more targeted, and a reference is provided for the subsequent establishment of the comprehensive transportation passenger service system collaborative operation optimization policy and scheme.
Description
Technical Field
The invention relates to the field of comprehensive transportation passenger service quality evaluation, in particular to a trip-chain-based joint passenger service evaluation method and device.
Background
The urban development can not leave traffic, convenient traffic is kept between the urban development and other cities with higher development levels, and the economic development of the cities can be indirectly driven, so that the evaluation of the passenger traffic service quality between the cities is an important link of the urban development. In a conventional means, the passenger transport traffic service quality between two cities is judged, the number of direct tracks, the number of flights, the number of passenger transport shifts and the like between the two cities can be simply judged, the more the number of direct tracks, the number of flights and the number of passenger transport shifts is, the higher the traffic service quality between the two cities is, but the judgment is too simple, strictly speaking, the judgment of the method is only the direct degree between the two cities, the direct degree is only one of influence factors of the passenger transport traffic service quality between the two cities, and the comprehensive traffic passenger transport service quality between the cities can not be accurately and comprehensively evaluated only through the research on the direct degree.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect that the comprehensive traffic passenger service quality evaluation between cities is relatively comprehensive in the prior art, so that a trip passenger service evaluation method and device based on a trip chain are provided.
The invention provides a trip chain-based joint passenger service evaluation method, which comprises the following steps: acquiring first travel data of a plurality of travel paths between a first preset position and a second preset position; calculating path characteristics between a first preset position and a second preset position according to the first travel data of each travel path; and calculating and analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position.
Optionally, the trip chain-based online passenger service assessment method provided by the invention further includes: acquiring second travel data of a travel route taking the first preset position as a starting point and/or an end point; calculating a comprehensive evaluation grade of the travel route taking the first preset position as a starting point and/or a terminal point according to the second travel data; and calculating the comprehensive transportation passenger transport service quality of the first preset position according to the comprehensive evaluation levels of the travel paths taking the first preset position as a starting point and/or a finishing point, the number of the travel paths corresponding to different comprehensive evaluation levels and the weight values corresponding to the comprehensive evaluation levels.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the step of calculating a comprehensive evaluation level of a travel route with the first preset position as a starting point and/or an ending point according to the second travel data includes: calculating a preset evaluation index of the travel path according to the second travel data of each travel path; establishing a whitening number matrix according to preset evaluation indexes of each travel path; carrying out dimensionless processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index; calculating characteristic values of the preset evaluation indexes corresponding to the comprehensive evaluation grades according to the preset evaluation indexes subjected to non-dimensionalization processing and preset index threshold values corresponding to different comprehensive evaluation grades; calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value; constructing a grey whitening function according to the attribute of a preset evaluation index; calculating the clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function; and determining the comprehensive evaluation level of the travel path according to the clustering coefficient.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the route characteristics between the first preset position and the second preset position include a low-speed delay route weighted value, and the step of calculating the route characteristics between the first preset position and the second preset position according to the first travel data of the travel route includes: calculating the average travelling speed of each travelling path according to the first travelling data of each travelling path; and calculating a low-speed delay path weighted value between the first preset position and the second preset position according to the average travel speed of each travel path, the range to which the average travel speed belongs and the weighted value corresponding to the range to which the average travel speed belongs.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the path characteristic between the first preset position and the second preset position includes a continuous delay path weighted value, and the step of calculating the path characteristic between the first preset position and the second preset position according to the first travel data of the travel path includes: acquiring a main transportation mode and a connection mode of each travel route, and a travel starting point and a travel ending point of the main transportation mode in each travel route; calculating the connection time ratio of each travel route according to the first travel data of each travel route, the travel starting point and the travel end point of the main transportation mode; and calculating a connection delay path weighted value between the first preset position and the second preset position according to the corresponding weights of the connection mode, the connection time ratio, the range of the connection time ratio and the range of the connection time ratio of each travel path.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the path characteristic between the first preset position and the second preset position includes a transfer delay path weighted value, and the step of calculating the path characteristic between the first preset position and the second preset position according to the first travel data of the travel path includes: calculating transfer times, transfer time and transfer time ratio of each travel route according to the first travel data of each travel route; and calculating a transfer delay path weighted value between the first preset position and the second preset position according to the transfer times, the transfer time ratio, the range of the transfer times, the weight corresponding to the range of the transfer times, the range of the transfer time, the weight corresponding to the range of the transfer time, the range of the transfer time ratio and the weight corresponding to the range of the transfer time of each travel path.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the path characteristics between the first preset position and the second preset position include travel mode diversity, and the step of calculating the path characteristics between the first preset position and the second preset position according to the first travel data of the travel path includes: calculating a comprehensive evaluation grade of each travel path according to the first travel data of each travel path; determining a travel mode combination between a first preset position and a second preset position according to travel data of each travel path, wherein each travel mode combination corresponds to at least one piece of travel data; and determining the travel mode diversity between the first preset position and the second preset position according to the average travel time and the comprehensive evaluation level of the travel data corresponding to each travel mode combination.
Optionally, in the method for evaluating a joint passenger service based on a travel chain provided by the present invention, the step of calculating a comprehensive evaluation level of each travel route according to the first travel data of each travel route includes: calculating a preset evaluation index of the travel path according to the first travel data of each travel path; establishing a whitening number matrix according to preset evaluation indexes of each travel path; carrying out dimensionless processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index; calculating characteristic values of the preset evaluation indexes corresponding to the comprehensive evaluation grades according to the preset evaluation indexes subjected to non-dimensionalization processing and preset index threshold values corresponding to different comprehensive evaluation grades; calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value; constructing a grey whitening function according to the attribute of a preset evaluation index; calculating the clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function; and determining the comprehensive evaluation level of the travel path according to the clustering coefficient.
The invention provides a trip chain-based joint passenger service evaluation device, which comprises: the trip data acquisition module is used for acquiring first trip data of a plurality of trip paths between a first preset position and a second preset position; the route characteristic calculation module is used for calculating route characteristics between a first preset position and a second preset position according to first travel data of the travel route; the trip chain-based joint passenger service evaluation method is used for calculating the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position.
A third aspect of the present invention provides a computer apparatus comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to perform the method for assessing a trip-chain based intermodal transportation service as provided by the first aspect of the present invention.
A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the trip-chain-based online passenger service assessment method according to the first aspect of the present invention.
The technical scheme of the invention has the following advantages:
1. the invention provides a trip chain-based joint passenger service evaluation method, which comprises the steps of firstly obtaining first trip data of a plurality of paths between a first preset position and a second preset position, then calculating the path characteristics between the first preset position and the second preset position, finally analyzing the transportation quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position, when the comprehensive transportation passenger service quality is analyzed by implementing the invention, the analysis result is more comprehensive by combining a plurality of path characteristics of the first travel data, in addition, the comprehensive transportation passenger transport service quality between two specific positions can be obtained by implementing the method, the analysis result is more targeted, and reference is provided for the subsequent establishment of the comprehensive transportation passenger transport system collaborative operation optimization policy and scheme.
2. According to the method for evaluating the joint passenger service based on the travel chain, provided by the invention, the second travel data of the travel route taking the first preset position as the starting point and/or the ending point are obtained, then the comprehensive evaluation level of each travel route is calculated according to the second travel data, and finally the comprehensive transportation passenger service quality of the first preset position is analyzed according to the comprehensive evaluation level of each travel route, the number of travel routes corresponding to different comprehensive evaluation levels and the weight corresponding to each comprehensive evaluation level.
3. The invention provides a trip chain-based joint passenger service evaluation device, which firstly obtains first trip data of a plurality of paths between a first preset position and a second preset position, then calculating the path characteristics between the first preset position and the second preset position, finally analyzing the passenger transport service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position, when the comprehensive transportation passenger service quality is analyzed by implementing the invention, the analysis result is more comprehensive by combining a plurality of path characteristics of the first travel data, in addition, the comprehensive transportation passenger service quality of the road section between two specific positions can be obtained by implementing the method, the analysis result is more targeted, and reference is provided for the subsequent establishment of the comprehensive transportation passenger system collaborative operation optimization policy and scheme.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a trip-chain-based method for evaluating a joint passenger service according to an embodiment of the present invention;
fig. 2 is a flowchart of another specific example of a trip-chain-based method for evaluating a joint passenger service according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a specific example of calculating a comprehensive evaluation level of a travel route according to an embodiment of the present invention;
fig. 4 is a flowchart of another specific example of a trip-chain-based method for evaluating a joint passenger service according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating still another specific example of a trip-chain-based method for evaluating a joint passenger service according to an embodiment of the present invention;
fig. 6 is a schematic block diagram of a specific example of the trip-chain-based online passenger service evaluation device in the embodiment of the present invention;
FIG. 7 is a functional block diagram of a specific example of a computer device provided in an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In the description of the present invention, it should be noted that the terms "first", "second", and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment of the invention provides a trip chain-based joint passenger service evaluation method, as shown in fig. 1, comprising the following steps:
step S10: first travel data of a plurality of travel paths between a first preset position and a second preset position are obtained. The travel data of one travel path form a travel chain.
In a specific embodiment, the first preset position and the second preset position can be any two places, but in the embodiment of the invention, the analysis is mainly performed on the quality of the comprehensive intercity transportation passenger service, so that the selected first preset position and the selected second preset position belong to two cities or two provinces respectively. In practical situations, there are various manners from the first preset position to the second preset position, and therefore, when the comprehensive transportation passenger service quality between the first preset position and the second preset position is researched, first travel data of a plurality of travel routes need to be acquired, and the plurality of routes include various travel manners.
Step S20: and calculating the path characteristics between the first preset position and the second preset position according to the first travel data of each travel path.
In a particular embodiment, one or more path features between the first preset location and the second preset location may be calculated according to the research focus. Specifically, the route characteristics may include one or more of a low-speed delay route weighting value, a continuation delay route weighting value, a transfer delay route weighting value, travel pattern diversity, and the like.
Step S30: and calculating and analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position. The comprehensive transportation passenger service quality is an expression form of the cooperative operation condition of the passenger transport system, and the higher the comprehensive transportation passenger service quality is, the better the cooperative operation condition of the comprehensive transportation passenger transport system is.
In a specific embodiment, when there are multiple path features, a weight may be respectively assigned to each path feature according to the importance degree of each path feature, and the comprehensive transportation passenger service quality between the first preset location and the second preset location is comprehensively analyzed and evaluated according to the value of each path feature and the weight of each path feature.
The trip chain-based joint passenger service evaluation method provided by the embodiment of the invention firstly obtains first trip data of a plurality of paths between a first preset position and a second preset position, then calculating the path characteristics between the first preset position and the second preset position, finally analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position, when the embodiment of the invention is used for analyzing the comprehensive transportation passenger service quality, the analysis is carried out by combining a plurality of path characteristics of the first travel data, the obtained analysis result is more comprehensive, in addition, the comprehensive transportation passenger service quality of the road section between two specific positions can be obtained through the embodiment of the invention, the analysis result is more targeted, and reference is provided for the subsequent establishment of the comprehensive transportation passenger system collaborative operation optimization policy and scheme.
In an alternative embodiment, the path characteristic between the first preset position and the second preset position includes a low speed delay path weight, and as shown in fig. 2, when the path characteristic between the first preset position and the second preset position includes a low speed delay path weight, the step S20 specifically includes:
step S211: and calculating the average travelling speed of each travelling path according to the first travelling data of each travelling path.
Step S212: calculating a low-speed delay path weighted value between a first preset position and a second preset position according to the average travel speed of each travel path, the range to which the average travel speed belongs and the weighted value corresponding to the range to which the average travel speed belongs:
low speed delay path weight ═ Σ (120-t)VBi)+2×∑(100-tVCi)+3×∑(80-tVDi)，
Wherein, tVBiThe average travelling speed is (120km/h, 100 km/h)]Actual average travel speed, t, of travel paths within the rangeVCiThe average travelling speed is (100km/h, 80 km/h)]Reality of travel paths within rangeAverage travel speed, tVDiThe average travelling speed is (80km/h, 0)]Actual average travel speed of travel paths within the range.
In an alternative embodiment, the path characteristics between the first preset position and the second preset position include a continuous delay path weighted value, as shown in fig. 2, when the path characteristics between the first preset position and the second preset position include a continuous delay path weighted value, the step S20 specifically includes:
step S221: and acquiring the main transportation mode and the connection mode of each travel route, and the travel starting point and the travel ending point of the main transportation mode in each travel route. In a specific embodiment, the main transportation mode is the transportation mode with the longest travel distance among all transportation modes in the travel route. The connection mode is a mode of arriving at the starting point of travel of the main transportation mode, and comprises class line passenger transport, private cars, network appointment cars, urban and rural buses, rural passenger transport, urban public transportation, taxis and the like.
Step S222: and calculating the connection time ratio of each travel route according to the first travel data of each travel route, the travel starting point and the travel end point of the main transportation mode.
In the embodiment of the present invention, when calculating the connection time ratio, the time from the starting point of the travel route to the starting point of the main transportation mode and the time from the travel end point of the main transportation mode to the end point of the travel route are calculated according to the first travel data of each travel route, the sum of the time from the starting point of the travel route to the starting point of the main transportation mode and the time from the travel end point of the main transportation mode to the end point of the travel route is the connection time, and then the connection time ratio is calculated according to the ratio of the sum of the connection time and the travel time.
Step S223: calculating a connection delay path weighted value between the first preset position and the second preset position according to the corresponding weights of the connection mode, the connection time ratio, the range of the connection time ratio and the range of the connection time ratio of each travel path:
wherein R isfBiThe ratio of the continuous time is (5% -10%]Actual ratio of connection time, R, of travel routes within rangefCiThe ratio of the continuous time is (10% -20%]Actual ratio of connection time, R, of travel routes within rangefDiThe ratio of the continuous time is (20-100%]Actual connection time of the travel route within the range accounts for the ratio; mAiNumber of travel routes representing continuation mode as urban traffic mode, MBiNumber of travel routes indicating that the connection mode is the same-site transfer mode, MCiNumber of travel routes, M, representing a connection mode of multiple transit in a cityDiThe connection mode is represented by the number of the trip paths of the cross-region cars.
In an alternative embodiment, the path characteristic between the first preset position and the second preset position includes a transfer delay path weight, and when the path characteristic between the first preset position and the second preset position includes a transfer delay path weight, as shown in fig. 2, the step S20 includes:
step S231: and calculating the transfer times, the transfer time and the transfer time ratio of each travel route according to the first travel data of each travel route.
Step S232: calculating a transfer delay path weighted value between the first preset position and the second preset position according to the transfer times, the transfer time ratio, the range of the transfer times, the weight corresponding to the range of the transfer times, the range of the transfer time, the weight corresponding to the range of the transfer time, the range of the transfer time ratio and the weight corresponding to the range of the transfer time of each travel path:
wherein, TtBiFor transfer time is (30min, 45 min)]Actual transfer time, T, of travel route within rangetCiFor transfer time is (45min, 60 min)]Actual transfer time, T, of travel route within rangetDiThe actual transfer time of the travel route with the transfer time of more than 60min is obtained; rtBiThe transfer time is (5%, 10%]Actual transfer time ratio, R, of travel routes within rangetCiThe transfer time is (10%, 20%)]Actual transfer time ratio, R, of travel routes within rangetDiThe actual transfer time ratio of the travel route with the transfer time ratio of more than 20 percent is obtained; n is a radical ofBiIndicates 2 transfers, NCiIndicates transfer 3 times, NDiIndicating the number of transfers of 4 or more.
In an alternative embodiment, the path characteristic between the first preset position and the second preset position includes a travel mode diversity, and as shown in fig. 2, when the path characteristic between the first preset position and the second preset position includes a travel mode diversity, the step S20 includes:
step S241: and calculating a comprehensive evaluation grade of each travel path according to the first travel data of each travel path, wherein in a specific embodiment, the comprehensive evaluation grade of each travel path comprises A, B, C, D four grades.
Step S242: and determining a travel mode combination between the first preset position and the second preset position according to the travel data of each travel route, wherein each travel mode combination corresponds to at least one piece of travel data.
Step S243: and determining the travel mode diversity between the first preset position and the second preset position according to the average travel time and the comprehensive evaluation level of the travel data corresponding to each travel mode combination.
In a specific embodiment, the average travel time of all travel routes in each travel mode combination and the average of the comprehensive evaluation grades of all travel routes in each travel mode combination can be calculated, and the closer the average travel time of each travel mode combination and the higher the weighted average grade are, the better the travel mode diversity between the first preset position and the second preset position is, and the higher the comprehensive transportation passenger transportation cooperative service level between the first preset position and the second preset position is.
In an optional embodiment, in the method for evaluating a joint passenger service based on a travel chain according to the embodiment of the present invention, as shown in fig. 3, the step S241 specifically includes:
step S2411: and calculating a preset evaluation index of the travel route according to the first travel data of each travel route.
In an embodiment of the present invention, the preset evaluation index of the travel path may be set according to an actual requirement, for example, in the embodiment of the present invention, the preset evaluation index of the travel path includes a full-distance average travel speed, a main travel mode time ratio, a following travel mode time ratio, a full-distance waiting time, a waiting time ratio, a full-distance transfer time, a transfer time ratio, and transfer times of the travel path.
Specifically, the average speed of the whole journey can be calculated according to the ratio of the total travel time to the distance of the shortest path of the self-driving vehicle, the average speed of the whole journey reflects the shortcut degree of the travel chain of the passenger, and the low average speed of the whole journey indicates that the delay is large. In a specific embodiment, the global average travel speed can be divided into four levels of excellent, good, medium and poor according to four intervals of (∞,120km/h ], (120km/h, 100km/h ], (100km/h, 80km/h ], (80km/h, 0 ]).
Specifically, the main travel mode refers to a travel mode with the largest travel distance ratio, and the time ratio of the main travel mode is calculated according to the ratio of the time used by the main travel mode to the total travel time. The time ratio of the main travel modes reflects the rationality of each travel mode combination in the travel route, and the low time ratio of the main travel modes indicates that the main travel modes are not strong in accessibility or have long time delay. In one embodiment, the time proportion of the main travel modes can be divided into four grades of superior, good, medium and poor according to four intervals of (100%, 95%, (95%, 90%, (90%, 80%, (80%, 0)).
Specifically, in the travel route, the other trips except the trip in the main trip mode are the following trips, and the following trip mode time ratio is calculated by the following formula:
Rf＝(tcity+tintercity+twait+ttransfer)/T，
tcitythe time (h), t) for the urban trip from the starting point to the external trip modeintercityTime (h), t) used for inter-city travel mode which is not the main travel modetransferLinking the total travel time (h), t) for the transfer between traffic modeswaitAnd (4) connecting the waiting total time (h) for the transfer among the transportation modes, wherein T is the total travel time.
The accessibility and the convenience of public transport travel can be reflected by the time proportion of the continuous travel mode. In one embodiment, the following travel mode time ratios can be classified into four grades of superior, good, medium and poor according to four intervals of (0, 5%, (5%, 10%, (10%, 20%, (20%, 100%)).
Specifically, the whole-journey waiting time is the vehicle night time, and in a specific embodiment, due to the particularity of the transportation mode, the whole-journey waiting time of the roads and the railways can be divided into four grades of good, middle and poor according to four intervals of (0,30min ], (30min, 45min ], (45min, 60min ], (60min, ∞), and the whole-journey waiting time of the aviation and the water transportation can be divided into four grades of good, middle and poor according to (0, 1h ], (1h, 1.5h ], (1.5h, 2h ], (2h, ∞).
Specifically, the whole-journey waiting time ratio can be calculated according to the ratio of the whole-journey waiting time to the total time of the whole-journey, and in one embodiment, the whole-journey waiting time ratio can be divided into four levels of priority, good, middle and poor according to four intervals of (0, 5%, (5%, 10%, (10%, 20%, (20%, 100%).
Specifically, the whole transfer time is the sum of the joining time and the waiting time when the transfer is performed in each transportation travel mode in the travel route. In one embodiment, the whole transfer time can be divided into four levels of good, medium and bad according to (0,30min ], (30min, 45min ], (45min, 60min ], (60min, ∞).
Specifically, the transfer time ratio can be calculated according to the ratio of the whole-journey transfer time to the whole-journey travel total time, and in one embodiment, the whole-journey waiting time ratio can be divided into four grades of priority, good, middle and poor according to four intervals of (0, 5% ], (5%, 10% ]), (10%, 20% ]), (20%, 100% ]).
Specifically, the transfer times include the sum of the transfer times between the same transportation means and the transfer times between different transportation means, and the transfer times may reflect the convenience of travel, and in one embodiment, the transfer times may be classified into four levels of good, medium, and bad according to four intervals of (0,1], (1, 2], (2, 3], (3, ∞).
Step S2412: establishing a whitening number matrix according to preset evaluation indexes of each travel path:
di＝[d1 d2 … di]，
wherein d isiAnd an index value representing the ith preset evaluation index.
Step S2413: and carrying out non-dimensionalization processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index, and compressing the data between [0, 1 ].
Step S2414: and calculating the characteristic value of each preset evaluation index corresponding to each comprehensive evaluation grade according to the preset evaluation index after the non-dimensionalization processing and the preset index threshold corresponding to different comprehensive evaluation grades.
Step S2415: calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value:
wherein the content of the first and second substances,
a weight indicating a kth evaluation level of an ith preset evaluation index,
and m represents the number of the preset evaluation indexes, and in the embodiment of the invention, the value of m is 8.
Step S2416: and constructing a grey whitening function according to the attribute of the preset evaluation index.
The upper limit measure whitening weight function is expressed as f [ d (1), d (2), - ], and the calculation formula is as follows:
wherein d (1) represents the characteristic value of the preset index grade A, and d (2) represents the characteristic value of the preset index grade B;
the whitening weight function of the moderate measure is marked as f [ d (1), d (2), -, d (4) ], and the calculation formula is as follows:
wherein D (4) represents a characteristic value of a preset index level D;
the lower limit measure whitening weight function is marked as f < - >, -, d (3), d (4), and the calculation formula is as follows:
wherein d (3) represents a feature value of the preset index level C.
Step S2417: calculating the clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function:
wherein σkA sum of clustering coefficients representing the evaluation indexes with respect to the k-th evaluation level,
and representing the function value of the ith preset evaluation index in the whitening function of the kth level.
Step S2418: and determining the comprehensive evaluation grade of the travel path according to the clustering coefficient, wherein the evaluation grade corresponding to the maximum clustering coefficient is the final evaluation result of the travel path.
In an optional embodiment, as shown in fig. 4, the method for evaluating a joint passenger service based on a trip chain according to an embodiment of the present invention further includes:
step S40: and acquiring second travel data of the travel route taking the first preset position as a starting point and/or an end point. In a specific embodiment, when analyzing the integrated transportation passenger service quality at the first preset location, only the travel data of the travel route with the first preset location as the starting point may be obtained, or only the travel data of the travel route with the first preset location as the end point may be obtained, the travel quality analysis result at the first preset location is obtained according to the travel data of the travel route with the first preset location as the starting point, the reachability quality analysis result at the first preset location is obtained according to the travel data of the travel route with the first preset location as the end point, although both are part of the integrated transportation passenger service quality, in practical application, there may be a certain area, although the reachability quality is qualified, the travel quality is poor, so in order to perform integrated analysis on the integrated transportation passenger service quality at the first preset location, the travel data of the travel route with the first preset position as the starting point and the ending point can be simultaneously acquired, so that the comprehensive transportation passenger service quality of the first preset position is analyzed.
In a specific embodiment, when the quality of the integrated transportation and passenger service between the first preset position and the second preset position is poor, in order to further determine whether the quality of the integrated transportation and passenger service of the first preset position is in problem, the quality of the integrated transportation and passenger service of the second preset position is in problem, or the cross-linking between the first preset position and the second preset position is in problem, the first preset position and the second preset position can be respectively researched, so that the location where the problem is located is accurately positioned.
In the embodiment of the present invention, the first preset position is considered as an example. When the comprehensive transportation passenger service quality at the first preset position is analyzed, the second travel data of the travel route with the first preset position as the starting point and/or the ending point can be obtained, and if the travel quality of the travel route with the first preset position as the starting point and/or the ending point is generally poor, the problem of the comprehensive transportation passenger service quality at the first preset position is shown.
Step S50: and calculating the comprehensive evaluation grade of the travel route taking the first preset position as a starting point and/or an end point according to the second travel data.
In a specific embodiment, the second travel data can be directly analyzed to obtain the comprehensive transportation passenger service quality at the first preset position, but in the embodiment of the invention, the evaluation grades of the travel routes with the first preset position as a starting point or an end point are calculated according to the second travel data, the travel qualities of the travel routes are quantized, so that the data generated in the analysis process can show the travel qualities more intuitively, the second travel data is preliminarily analyzed to obtain the comprehensive evaluation grade of the travel route corresponding to the second travel data, and when the travel routes corresponding to the second travel data are subsequently analyzed in other aspects, only research is needed on the basis of the comprehensive evaluation grade of the travel route, analysis and calculation on the second travel data are not needed again, and the analysis efficiency is improved.
Step S60: calculating the comprehensive transportation passenger service quality of the first preset position according to the comprehensive evaluation levels of all travel paths taking the first preset position as a starting point and/or a finishing point, the number of the travel paths corresponding to different comprehensive evaluation levels and the weight values corresponding to all the comprehensive evaluation levels:
the integrated transportation passenger service quality of the first preset position is (the number of the a-level travel routes × 1+ the number of the B-level travel routes × 2+ the number of the C-level travel routes × 3+ the number of the D-level travel routes × 4)/the total number of the travel routes
In the embodiment of the invention, the comprehensive transportation passenger service quality of the first preset position refers to the travel quality when the first preset position is taken as a starting point or an ending point, and the transportation convenience degree at the first preset position can be indirectly reflected through the comprehensive transportation passenger service quality of the first preset position.
According to the trip chain-based joint passenger service evaluation method provided by the embodiment of the invention, the second trip data of the trip route taking the first preset position as the starting point and/or the ending point is obtained, then the comprehensive evaluation grade of each trip route is calculated according to the second trip data, and finally the comprehensive transportation passenger service quality of the first preset position is analyzed according to the comprehensive evaluation grade of each trip route, the number of trip routes corresponding to different comprehensive evaluation grades and the weight corresponding to each comprehensive evaluation grade.
In an alternative embodiment, as shown in fig. 5, the step S50 specifically includes:
step S51: calculating a preset evaluation index of the travel path according to the second travel data of each travel path;
step S52: establishing a whitening number matrix according to preset evaluation indexes of each travel path;
step S53: carrying out dimensionless processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index;
step S54: calculating characteristic values of the preset evaluation indexes corresponding to the comprehensive evaluation grades according to the preset evaluation indexes subjected to non-dimensionalization processing and preset index threshold values corresponding to different comprehensive evaluation grades;
step S55: calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value;
step S56: constructing a grey whitening function according to the attribute of a preset evaluation index;
step S57: calculating the clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function;
step S58: and determining the comprehensive evaluation level of the travel path according to the clustering coefficient.
The specific method for calculating the comprehensive evaluation level of the travel route is detailed in the steps S2411 to 2418.
In a specific embodiment, when analyzing the inter-city integrated transportation passenger service quality, besides the integrated transportation passenger service quality between the first preset location and the second preset location in the above steps, or performing fixed-point analysis on the integrated transportation passenger service quality at the first preset location, the method further includes analyzing a trip hot spot, where the integrated transportation passenger service quality at the trip hot spot is an object needing important attention, and therefore identifying the trip hot spot is an important step of analyzing the integrated transportation passenger service quality.
In an optional embodiment, the trip hotspot includes an airline trip demand hotspot, and the step of identifying the airline trip demand hotspot includes: counting passenger traffic of traveling passengers at the airports on the basis of latitude and longitude information of the area where the airports are located, sequencing the passenger traffic of each airport by taking 1 day as a statistical unit, and determining the top 50% of airports as the hot spots of aviation travel demands.
In an optional embodiment, the trip hotspot includes a railway trip demand hotspot, and the step of identifying the railway trip demand hotspot includes: the method comprises the steps of counting passenger traffic of traveling passengers of the railway stations on the basis of longitude and latitude information of an area where the railway stations (including high-speed railways and ordinary railways) are located, sequencing the passenger traffic of each railway station by taking 1 day as a statistical unit, and determining the first 50% of the railway stations as railway traveling demand hotspots.
In an optional embodiment, the trip hotspot includes a water trip demand hotspot, and the step of identifying the water trip demand hotspot includes: and (3) counting the passenger flow of the passengers going out of the ports on the basis of the latitude and longitude information of the region where the ports are located, sequencing the passenger flow of each port by taking 1 day as a statistical unit, and determining the first 50 percent of the ports as the hot spots of the water transportation trip demand.
In an optional embodiment, the travel hotspot includes a highway travel demand hotspot, and the step of identifying the highway travel demand hotspot includes: counting passenger traffic of the long-distance passenger stations on the basis of longitude and latitude information of the region where the long-distance passenger stations are located, sequencing the passenger traffic of each long-distance passenger station by taking 1 day as a statistical unit, and determining the first 50% of the long-distance passenger stations as highway travel demand hot spots.
In a specific embodiment, when analyzing the quality of the inter-city integrated transportation passenger service, the method further comprises the following steps: respectively extracting the track starting points of travel paths for traveling in the modes of aviation, railway, water transportation and highway, and calculating the radiation range of each airport, railway station, port and long-distance passenger station and the travel mode proportion in each radiation distance.
In a specific embodiment, when analyzing the quality of the inter-city integrated transportation passenger service, the method further comprises the following steps: and extracting transfer travel sections in the travel path, counting stations with the transfer number (the number of passengers between roads, water transportation, railways and aviation modes or between different travel sections of the same travel mode) accounting for more than 50% of the total passenger flow of the current passenger station/port/railway station/airport by taking 1 day as a statistical unit, and determining the stations as the hot spot of the passenger joint travel transfer demand.
By implementing the embodiment of the invention, the comprehensive transportation passenger service quality of intercity transportation can be comprehensively, accurately and comprehensively analyzed.
Example 2
An embodiment of the present invention provides a trip chain-based online passenger service evaluation device, as shown in fig. 6, including:
the travel data acquiring module 10 is configured to acquire first travel data of a plurality of travel paths between a first preset position and a second preset position, and the details of the first travel data are described in the above step S10.
The path characteristic calculating module 20 is configured to calculate a path characteristic between the first preset position and the second preset position according to the first travel data of the travel path, which is described in detail in the above step S20.
The trip-chain-based joint passenger service evaluation module 30 is configured to calculate a comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position, and the details are as described in the above step S30.
The trip chain-based joint passenger service evaluation device provided by the embodiment of the invention firstly obtains first trip data of a plurality of paths between a first preset position and a second preset position, then calculating the path characteristics between the first preset position and the second preset position, finally analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position, when the embodiment of the invention is implemented to analyze the comprehensive transportation passenger service quality, the analysis result is more comprehensive by combining a plurality of path characteristics of the first travel data, in addition, by implementing the embodiment of the invention, the comprehensive transportation passenger service quality of the trip between two specific positions can be obtained, the analysis result is more targeted, and reference is provided for the subsequent establishment of the comprehensive transportation passenger system collaborative operation optimization policy and scheme.
Example 3
An embodiment of the present invention provides a computer device, as shown in fig. 7, the computer device mainly includes one or more processors 41 and a memory 42, and fig. 7 takes one processor 41 as an example.
The computer device may further include: an input device 43 and an output device 44.
The processor 41, the memory 42, the input device 43 and the output device 44 may be connected by a bus or other means, and fig. 7 illustrates the connection by a bus as an example.
The processor 41 may be a Central Processing Unit (CPU). The Processor 41 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The memory 42 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the trip-chain-based intermodal transportation service evaluation device, and the like. Further, the memory 42 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 42 may optionally include memory located remotely from processor 41, which may be connected to a trip chain-based intermodal transportation services evaluation device over a network. The input device 33 may receive a calculation request (or other numeric or character information) entered by a user and generate key signal inputs relating to the trip chain-based intermodal service evaluation device. The output device 44 may include a display device such as a display screen for outputting the calculation result.
Example 4
An embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer-readable storage medium stores computer-executable instructions, where the computer-executable instructions may execute the trip chain-based method for evaluating a passenger transport service in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (11)
1. A trip chain-based joint passenger service assessment method is characterized by comprising the following steps:
acquiring first travel data of a plurality of travel paths between a first preset position and a second preset position;
calculating a path characteristic between the first preset position and the second preset position according to the first travel data of each travel path;
and calculating and analyzing the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position.
2. The trip chain-based intermodal transport service assessment method according to claim 1, further comprising:
acquiring second travel data of a travel route taking the first preset position as a starting point and/or an end point;
calculating a comprehensive evaluation grade of the travel route taking the first preset position as a starting point and/or a terminal point according to the second travel data;
and calculating the comprehensive transportation passenger service quality of the first preset position according to the comprehensive evaluation level of each travel route taking the first preset position as a starting point and/or a finishing point, the number of travel routes corresponding to different comprehensive evaluation levels and the weight value corresponding to each comprehensive evaluation level.
3. The trip chain-based intermodal transportation service assessment method according to claim 2, wherein the step of calculating a comprehensive evaluation grade of the trip route with the first preset position as a starting point and/or an end point according to the second trip data comprises:
calculating a preset evaluation index of the travel path according to the second travel data of each travel path;
establishing a whitening number matrix according to preset evaluation indexes of each travel path;
carrying out non-dimensionalization processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index;
calculating characteristic values of the preset evaluation indexes corresponding to the comprehensive evaluation grades according to the preset evaluation indexes subjected to non-dimensionalization processing and preset index threshold values corresponding to different comprehensive evaluation grades;
calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value;
constructing a grey whitening function according to the attribute of the preset evaluation index;
calculating a clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function;
and determining the comprehensive evaluation level of the travel path according to the clustering coefficient.
4. The trip chain-based intermodal transport services assessment method according to claim 1, wherein the path characteristics between the first preset location and the second preset location include low speed delay path weighting values,
the step of calculating the path characteristics between the first preset position and the second preset position according to the first travel data of the travel path comprises the following steps:
calculating the average travelling speed of each travelling path according to the first travelling data of each travelling path;
and calculating a low-speed delay path weighted value between a first preset position and a second preset position according to the average travelling speed of each travelling path, the range to which the average travelling speed belongs and the weighted value corresponding to the range to which the average travelling speed belongs.
5. The method of claim 1, wherein the route characteristics between the first predetermined location and the second predetermined location comprise sequential delay route weights,
the step of calculating the path characteristics between the first preset position and the second preset position according to the first travel data of the travel path comprises the following steps:
acquiring a main transportation mode and a connection mode of each travel route, and a travel starting point and a travel ending point of the main transportation mode in each travel route;
calculating the connection time ratio of each travel route according to the first travel data of each travel route, the travel starting point and the travel end point of the main transportation mode;
and calculating a connection delay path weighted value between the first preset position and the second preset position according to the connection mode, the connection time ratio, the range to which the connection time ratio belongs and the weight corresponding to the range to which the connection time ratio belongs of each travel path.
6. The trip chain-based intermodal transport services assessment method according to claim 1, wherein the path characteristics between the first preset location and the second preset location include transfer delay path weighting values,
the step of calculating the path characteristics between the first preset position and the second preset position according to the first travel data of the travel path comprises the following steps:
calculating transfer times, transfer time and transfer time ratio of each travel route according to the first travel data of each travel route;
and calculating a transfer delay path weighted value between the first preset position and the second preset position according to the transfer times, the transfer time ratio, the range of the transfer times, the weight corresponding to the range of the transfer times, the range of the transfer time, the weight corresponding to the range of the transfer time, the range of the transfer time ratio and the weight corresponding to the range of the transfer time of each travel path.
7. The trip chain-based intermodal transport services assessment method according to claim 1, wherein the path characteristics between the first preset location and the second preset location include travel pattern diversity,
the step of calculating the path characteristics between the first preset position and the second preset position according to the first travel data of the travel path comprises the following steps:
calculating a comprehensive evaluation grade of each travel path according to the first travel data of each travel path;
determining a travel mode combination between a first preset position and a second preset position according to travel data of each travel path, wherein each travel mode combination corresponds to at least one piece of travel data;
and determining the travel mode diversity between the first preset position and the second preset position according to the average travel time and the comprehensive evaluation level of the travel data corresponding to each travel mode combination.
8. The trip chain-based joint passenger service evaluation method according to claim 7, wherein the step of calculating the comprehensive evaluation level of each travel route according to the first travel data of each travel route comprises:
calculating a preset evaluation index of the travel path according to the first travel data of each travel path;
establishing a whitening number matrix according to preset evaluation indexes of each travel path;
carrying out non-dimensionalization processing on each preset evaluation index of the travel path according to the attribute of the preset evaluation index;
calculating characteristic values of the preset evaluation indexes corresponding to the comprehensive evaluation grades according to the preset evaluation indexes subjected to non-dimensionalization processing and preset index threshold values corresponding to different comprehensive evaluation grades;
calculating the weight of each preset evaluation index in each comprehensive evaluation grade according to the characteristic value;
constructing a grey whitening function according to the attribute of the preset evaluation index;
calculating a clustering coefficient of each evaluation index relative to each comprehensive evaluation grade according to the weight and the grey whitening function;
and determining the comprehensive evaluation level of the travel path according to the clustering coefficient.
9. The utility model provides a joint journey passenger service evaluation device based on trip chain which characterized in that includes:
the trip data acquisition module is used for acquiring first trip data of a plurality of trip paths between a first preset position and a second preset position;
the route characteristic calculation module is used for calculating route characteristics between the first preset position and the second preset position according to first travel data of the travel route;
and the trip-chain-based joint passenger service evaluation module is used for calculating the comprehensive transportation passenger service quality between the first preset position and the second preset position according to the path characteristics between the first preset position and the second preset position.
10. A computer device, comprising:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to perform the method for assessing trip chain based intermodal transportation services according to any one of claims 1 to 8.
11. A computer-readable storage medium storing computer instructions for causing a computer to perform the method for assessing trip-chain based intermodal transportation services according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011230484.0A CN112365042A (en) | 2020-11-06 | 2020-11-06 | Trip passenger service evaluation method and device based on trip chain |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011230484.0A CN112365042A (en) | 2020-11-06 | 2020-11-06 | Trip passenger service evaluation method and device based on trip chain |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112365042A true CN112365042A (en) | 2021-02-12 |
Family
ID=74508884
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011230484.0A Pending CN112365042A (en) | 2020-11-06 | 2020-11-06 | Trip passenger service evaluation method and device based on trip chain |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112365042A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2932566A1 (en) * | 2021-07-14 | 2023-01-20 | Garcia Garcia Eric | Destination Management Procedure (Machine-translation by Google Translate, not legally binding) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110705848A (en) * | 2019-09-18 | 2020-01-17 | 交通运输部公路科学研究所 | Comprehensive traffic service evaluation method and device based on individual trip chain |
| CN111160731A (en) * | 2019-12-13 | 2020-05-15 | 东南大学 | Air-rail joint service comprehensive evaluation method based on passenger perception |
-
2020
- 2020-11-06 CN CN202011230484.0A patent/CN112365042A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110705848A (en) * | 2019-09-18 | 2020-01-17 | 交通运输部公路科学研究所 | Comprehensive traffic service evaluation method and device based on individual trip chain |
| CN111160731A (en) * | 2019-12-13 | 2020-05-15 | 东南大学 | Air-rail joint service comprehensive evaluation method based on passenger perception |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2932566A1 (en) * | 2021-07-14 | 2023-01-20 | Garcia Garcia Eric | Destination Management Procedure (Machine-translation by Google Translate, not legally binding) |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107036617B (en) | Travel route planning method and system combining taxi and subway | |
| CN107316098B (en) | Automobile leasing point addressing method based on user behavior analysis | |
| CN110705848B (en) | Comprehensive traffic service evaluation method and device based on individual trip chain | |
| CN105844362B (en) | Urban traffic comprehensive trip decision-making device | |
| CN107609677A (en) | A kind of customization public bus network planing method based on taxi GPS big datas | |
| CN102567389B (en) | Combined traffic network forming method and equipment as well as path searching method and equipment | |
| CN110415513B (en) | Method, system and electronic device for publishing bus lane service index | |
| Axelsson et al. | Truck platooning business case analysis | |
| CN112365042A (en) | Trip passenger service evaluation method and device based on trip chain | |
| Archetti et al. | On-demand public transportation | |
| Feng et al. | Choices of intercity multimodal passenger travel modes | |
| CN116502960B (en) | Station area TOD development potential evaluation method, system and electronic equipment | |
| CN111126878B (en) | Urban traffic operation evaluation method based on ecological index | |
| CN107545314B (en) | Method and device for sequencing public travel routes | |
| CN110567474B (en) | Taxi real-time tour route recommendation system and method based on big data | |
| Harmadi et al. | How does congestion matter for Jakarta’s citizens | |
| CN109584546B (en) | Method for determining departure flow threshold of quick-conventional bus sharing lane | |
| CN111275970B (en) | Optimal route planning method considering real-time bus information | |
| CN114021295A (en) | Multi-mode carriageway fine setting method based on branch-and-bound method | |
| CN112632374A (en) | Resident travel mode selection analysis method considering customized bus | |
| CN110390556B (en) | Dynamic formulating method for bus fare of variable line | |
| Zeng et al. | Study on a New Mobility Pattern Based on Autonomous Road Transportation System | |
| CN113205213B (en) | Public transport evaluation method and system based on internet map data | |
| Chen et al. | Several thoughts on GHG emission reduction and traffic congestion control in urban transport | |
| Rachmadina et al. | Analysis of the Choice of Commuter Line Electric Rail Train (KRL) Modes and Transjakarta Buses for the Bekasi City-East Jakarta Route |
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 |