CN114547131A - Integrated traffic distribution mode OD (origin-destination) acquisition method considering joint trip - Google Patents

Integrated traffic distribution mode OD (origin-destination) acquisition method considering joint trip Download PDF

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CN114547131A
CN114547131A CN202210008984.2A CN202210008984A CN114547131A CN 114547131 A CN114547131 A CN 114547131A CN 202210008984 A CN202210008984 A CN 202210008984A CN 114547131 A CN114547131 A CN 114547131A
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华雪东
雷惠莹
王炜
魏雪延
赵德
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Abstract

The invention discloses a comprehensive traffic sub-mode OD acquisition method considering joint travel, which comprises four steps of data acquisition, utility calculation, proportion analysis and OD acquisition, wherein the travel OD matrix data in the range of an analysis area is acquired, the travel utility of all feasible travel mode combinations between two places is calculated according to a formula, the travel proportion of all feasible travel mode combinations between the two places is calculated on the basis, the sub-mode OD matrix of the travel mode between the two places is finally obtained by calculation, the possibility of joint travel between cities is considered by taking actual data as support, the method has strong practicability and operability, has important significance for carrying out comprehensive traffic travel mode division prediction and traffic planning, and provides practical scientific basis for planning and transformation of urban inter-group passenger transport hubs and scheduling and optimization of inter-hub transport capacity, the supply capacity and the quality of the transportation service are improved more scientifically and reasonably, and the travel experience of passengers is improved.

Description

Integrated traffic distribution mode OD (origin-destination) acquisition method considering trip travel
Technical Field
The invention belongs to the field of comprehensive transportation, and particularly relates to a comprehensive transportation sub-mode OD obtaining method considering joint travel.
Background
With the continuous promotion of the urbanization process, the city form of the urban group appears in China and becomes mature day by day. The development of regional economy integration makes political, cultural and economic communication between cities in the urban group increasingly close, and with the rapid development of transportation modes such as high-speed rails and airplanes, people put forward higher requirements for urban group outgoing, so that a transportation service mode of passenger joint transportation is generated. The passenger joint journey transportation means that the passenger is subjected to overall planning and management by using multiple sections of journey of one or more traffic modes, so that the integrated transportation organization of the passenger is realized, and the transportation service mode of the continuity and convenience of the passenger trip is ensured. The appearance of the mode expands the travel range of residents in the urban group and brings changes of the hub passenger demand of the urban group. At present, the joint transportation of passengers in China is still in the starting stage, and the transportation facilities between hubs are not reasonably allocated according to the change of passenger demand brought by the joint passenger transportation. As an important ring of a comprehensive transportation service system, the combined transportation of passengers can synthesize the advantages of various travel modes, thereby effectively improving the comprehensive transportation efficiency and greatly improving the travel experience of the passengers. The development of the passenger intermodal transportation has important significance for the rapid promotion of the transportation of China, the construction and the perfection of the modern comprehensive transportation system and the construction of a transportation service system.
After years of theoretical research and practical exploration, scholars at home and abroad have conducted research on comprehensive transportation passenger travel behaviors and passenger joint transportation. Foreigners have Forinash C.V. and K oppelman F s, the travel mode selection behavior mechanism Aoife A of the passenger is researched based on the principle of the utility theory, the role of personal preference of the passenger in travel mode selection decision is researched by AherN.T 4, and the influence of personal attribute and attitude of the passenger on mode selection behavior is researched by Per Johansson and the like. In China, the method is like an NL model, an ML model, an MNL model, a mixed selection model and the like, but most of the methods are researched aiming at a single trip mode, the research on the multi-mode combined trip behaviors of urban group passengers is lacked, and the trip of the passengers not only comprises the single trip mode, but also comprises the multi-mode combined trip.
Disclosure of Invention
Aiming at the problem that most of the existing models are researched by aiming at a single trip mode and cannot be suitable for researching the multi-mode combined trip behavior of urban group passengers, the invention provides a comprehensive traffic distribution mode OD acquisition method considering the trip, by collecting travel OD matrix data in the area range to be analyzed and calculating the travel utility of all feasible travel mode combinations between two places according to a formula, on the basis, the travel proportion of all feasible travel mode combinations between two places is calculated, and finally, a sub-mode OD matrix of the travel modes between the two places is obtained through calculation, the practical data is taken as the support, the possibility of travel in a joint way between cities is considered, the practicability and operability are very strong, the method has important significance for carrying out division prediction and traffic planning of a comprehensive traffic trip mode, and provides practical scientific basis for planning and transformation of urban inter-group passenger transportation hubs and scheduling and optimization of transportation capacity among hubs.
In order to solve the above problems, the present invention adopts the following technical solutions.
A comprehensive traffic distribution mode OD obtaining method considering trip travel comprises the following steps:
step A, data acquisition: collecting travel data of n traffic areas within the area needing to be analyzed;
b, utility calculation: b, calculating the travel utility of all feasible travel mode combinations between the traffic area i and the traffic area j according to the data collected in the step A;
step C, proportion analysis: calculating the travel proportion of all feasible travel mode combinations between the traffic area i and the traffic area j by adopting the travel utility calculated in the step B;
step D, OD obtains: and D, combining the data acquired in the step A and the travel proportion calculated in the step C, and calculating to obtain a sub-mode OD matrix of the travel modes between the traffic area i and the traffic area j.
In a further technical scheme, the step A specifically comprises the following steps:
collecting travel OD matrixes in the region needing analysis:
Figure BDA0003458184930000021
wherein, gi,jThe travel demand from a traffic area i to a traffic area j is obtained, n is the total number of the traffic areas in the area range needing to be analyzed, i and j are integers larger than 0, i belongs to n, and j belongs to n;
acquiring the number N of feasible travel mode combinations between a traffic area i and a traffic area ji,j
Collecting the accumulated quantity of travel modes adopted in the kth feasible travel mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000022
Collecting the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000023
Collecting travel distance adopted by mth type in kth feasible travel mode combination between traffic area i and traffic area j
Figure BDA0003458184930000024
Collecting traffic area serial numbers transferred by the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000025
Wherein k is an integer greater than 0, andk≤Ni,j(ii) a m is an integer greater than 0, and
Figure BDA0003458184930000026
Figure BDA0003458184930000027
the values are 1, 2, 3 and 4, which respectively represent highway, railway, aviation and water transportation travel modes;
Figure BDA0003458184930000028
the unit is kilometer;
Figure BDA0003458184930000029
is an integer greater than 0, and
Figure BDA0003458184930000031
Figure BDA0003458184930000032
indicating that the endpoint is not to be changed; the transportation modes comprise highways, railways, aviation and water transportation.
In step B, the following formula is used to calculate the travel utility of the kth feasible travel mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000033
Figure BDA0003458184930000034
Wherein,
Figure BDA0003458184930000035
for distance utility function, representation is taken
Figure BDA0003458184930000036
Travel mode trip
Figure BDA0003458184930000037
Of a distanceTrip utility;
Figure BDA0003458184930000038
to transfer the utility function, express from
Figure BDA0003458184930000039
Travel mode is transferred to
Figure BDA00034581849300000310
Transfer utility of travel patterns.
In step C, the travel proportion of the kth feasible travel mode combination between the traffic zone i and the traffic zone j
Figure BDA00034581849300000311
Calculated using the formula:
Figure BDA00034581849300000312
wherein e is a natural base number, o is 1 or more and N or lessi,jThe number of the integer (c) of (d),
Figure BDA00034581849300000313
indicated as the o-th feasible travel pattern combination between traffic zone i and traffic zone j.
According to a further technical scheme, the step D specifically comprises the following steps:
step D1, initializing the sub-mode OD matrix: initializing the sub-mode OD matrix of the highway, the railway, the aviation and the water transportation, and dividing the highway into sub-modes OD1Matrix, railway mode OD2Matrix and aviation separation mode OD3Matrix and water movement mode OD4All elements in the matrix are set to 0, wherein,
Figure BDA00034581849300000314
Figure BDA00034581849300000315
Figure BDA0003458184930000041
Figure BDA0003458184930000042
wherein,
Figure BDA0003458184930000043
and
Figure BDA0003458184930000044
traffic volumes between a traffic area i and a traffic area j in a highway, a railway, an aviation and water transportation mode respectively;
step D2, performing load search in different modes:
the road mode is as follows: the data collected in the step A are searched in sequence from the traffic area i to the traffic area j, and when the data are searched in sequence, the data are transmitted to the traffic area j
Figure BDA0003458184930000045
And is
Figure BDA0003458184930000046
And is
Figure BDA0003458184930000047
Will be provided with
Figure BDA0003458184930000048
Is accumulated to
Figure BDA0003458184930000049
The above step (1);
the railway mode is as follows: the data collected in the step A are searched in sequence from the traffic area i to the traffic area j, and when the data are searched in sequence, the data are transmitted to the traffic area j
Figure BDA00034581849300000410
And is
Figure BDA00034581849300000411
And is
Figure BDA00034581849300000412
Will be provided with
Figure BDA00034581849300000413
Is accumulated to
Figure BDA00034581849300000414
The above step (1);
an aviation mode: the data collected in the step A) between the traffic area i and the traffic area j are searched in sequence when
Figure BDA00034581849300000415
And is
Figure BDA00034581849300000416
And is
Figure BDA00034581849300000417
Will be provided with
Figure BDA00034581849300000418
Is accumulated to
Figure BDA00034581849300000419
The above step (1);
water transportation mode: the data collected in the step A) between the traffic areas i and j are searched in sequence when
Figure BDA00034581849300000420
And is
Figure BDA00034581849300000421
And is
Figure BDA00034581849300000422
Will be provided with
Figure BDA00034581849300000423
Is accumulated to
Figure BDA00034581849300000424
The above step (1);
wherein p and q are respectively the serial numbers of the traffic areas, both p and q are integers larger than 0, and p belongs to n, and q belongs to n;
Figure BDA00034581849300000425
a traffic area serial number for transfer of the mth travel mode in the kth feasible travel mode combination from the traffic area p to the traffic area q;
Figure BDA00034581849300000426
the travel mode is adopted in the mth travel mode combination from the traffic area p to the traffic area q;
Figure BDA00034581849300000427
the trip proportion of the kth feasible trip mode combination between the traffic area p and the traffic area q; gp,qThe travel demands from the traffic area p to the traffic area q;
step D3, performing mode OD result arrangement: and D2, sorting the results of the sub-mode row quantity search in the step D2 to obtain a sub-mode OD matrix.
In step a, the cumulative number of travel modes used in the kth feasible travel mode combination from the traffic zone i to the traffic zone j
Figure BDA0003458184930000051
To pair
Figure BDA0003458184930000052
Counting, if the mode transfer occurs in the traffic area, not counting the travel mode conversion in the traffic area, only counting the travel mode leaving the traffic area at last
Figure BDA0003458184930000053
In (1).
Go toThe technical scheme of the steps is that in the step A, the accumulated quantity of the travel modes adopted in the kth feasible travel mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000054
To pair
Figure BDA0003458184930000055
Counting, if the same trip mode appears more than once in the feasible trip mode combination, counting according to the times of the appearance
Figure BDA0003458184930000056
In (1).
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
compared with the traditional NL model, ML model and the like, the comprehensive traffic sub-mode OD obtaining method considering the trip travel carries out utility calculation of all feasible travel schemes between two places based on scheme selection behavior data when a passenger carries out the trip travel between urban group hubs, obtains proportion analysis of all feasible travel schemes between the two places according to a formula on the basis, finally obtains a comprehensive traffic sub-mode OD matrix between the two places, considers the typical passenger trip travel scheme selection behavior data between cities based on actual data as support, and has higher accuracy and reliability compared with the traditional prediction method; meanwhile, the method has clear thinking in the whole process, has strong practicability and operability, provides a new thinking and a new method for obtaining the comprehensive transportation mode OD, has important significance for division prediction and traffic planning of the comprehensive transportation mode, provides practical scientific basis for planning and transformation of passenger transportation hubs among city groups and dispatching and optimization of transportation capacity among hubs, more scientifically and reasonably improves the supply capacity and quality of transportation service, improves the traveling experience of passengers, and better meets the high-quality, diversified and personalized traveling requirements of the passengers.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is further described below with reference to specific embodiments and the accompanying drawings.
Examples
The embodiment provides a method for acquiring an OD in a comprehensive traffic distribution mode in consideration of trip travel, as shown in fig. 1, the method includes the following steps:
step A, data acquisition: collecting travel OD matrixes in the region needing to be analyzed,
Figure BDA0003458184930000057
gi,jthe trip requirements from a traffic area i to a traffic area j are integers which are more than 0 and less than n, and n is the total number of the traffic areas in the area range needing to be analyzed;
collecting the number N of feasible travel mode combinations between a traffic area i and a traffic area ji,jCollecting the accumulated quantity of travel modes adopted in the kth feasible travel mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000061
Collecting the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000062
Collecting travel distance adopted by mth type in kth feasible travel mode combination between traffic area i and traffic area j
Figure BDA0003458184930000063
Collecting traffic area serial numbers transferred by the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure BDA0003458184930000064
Wherein k is an integer greater than 0 and k is not more than Ni,j(ii) a m is an integer greater than 0, and
Figure BDA0003458184930000065
Figure BDA0003458184930000066
the values are 1, 2, 3 and 4, which respectively represent the travel modes of highways, railways, aviation and water transportation;
Figure BDA0003458184930000067
the unit is kilometer;
Figure BDA0003458184930000068
is an integer greater than 0, and
Figure BDA0003458184930000069
is specially stipulated
Figure BDA00034581849300000610
Indicating that the endpoint is not to be changed; the trip data can be directly obtained from the statistical departments, the traffic departments and the like of the countries or the related regions/cities, and can also be directly downloaded or captured from the internet based on the big data technology, and the traffic modes comprise roads, railways, aviation and water transportation.
In this embodiment, 13 regions in northeast province of china are selected as the regions to be analyzed, and the travel OD matrix is as follows:
Figure BDA00034581849300000611
wherein, the names of the 13 traffic areas can be sequentially recorded as: full XX (traffic zone 1), high XX (traffic zone 2), sinking X1 (traffic zone 3), light XX (traffic zone 4), sinking X2 (traffic zone 5), glow XX (traffic zone 6), turbid XX (traffic zone 7), threxx (traffic zone 8), new XX (traffic zone 9), normal XX (traffic zone 10), healthy XX (traffic zone 11), large XX (traffic zone 12) and pacifying XX (traffic zone 13).
And then, acquiring feasible travel mode combinations among the traffic areas. Taking cell 5 to cell 12 as an example, the number N of feasible travel mode combinations between traffic zone 5 and traffic zone 125,123, itIn
Figure BDA00034581849300000612
Equal to 1, 1 respectively,
Figure BDA00034581849300000613
Figure BDA0003458184930000071
equal to 1, 2 respectively,
Figure BDA0003458184930000072
equal to 350KM, 312KM, 350KM respectively,
Figure BDA0003458184930000073
Figure BDA0003458184930000074
equal to 12, 12 respectively.
B, utility calculation; according to the data collected in the step A, calculating the travel utility of the kth feasible travel mode combination between the traffic area i and the traffic area j by adopting the following formula
Figure BDA0003458184930000075
Figure BDA0003458184930000076
Wherein,
Figure BDA0003458184930000077
for distance utility function, representation is taken
Figure BDA0003458184930000078
Travel mode trip
Figure BDA0003458184930000079
Trip utility of distance;
Figure BDA00034581849300000710
to transfer the utility function, express from
Figure BDA00034581849300000711
Travel mode is transferred to
Figure BDA00034581849300000712
Transfer utility of travel mode;
step C, proportion analysis: calculating the travel proportion of the kth feasible travel mode combination between the traffic area i and the traffic area j by adopting the step B
Figure BDA00034581849300000713
Figure BDA00034581849300000714
Wherein e is a natural base number, o is 1 or more and N or lessi,jThe number of the integer (c) of (d),
Figure BDA00034581849300000715
indicated as the o-th feasible travel pattern combination between traffic zone i and traffic zone j.
Step D, OD obtains: and C, calculating to obtain a scoring mode OD matrix by combining the data acquired in the step A and the travel proportion obtained by analyzing in the step C, and specifically comprising the following steps:
step D1, initializing the sub-mode OD matrix: road is divided into modes OD1Matrix, railway mode OD2Matrix and aviation separation mode OD3Matrix and water movement mode OD4Initializing matrix, dividing road into modes OD1Matrix, railway mode OD2Matrix and aviation separation mode OD3Matrix and water movement mode OD4All elements in the matrix are set to 0, specifically:
Figure BDA00034581849300000716
Figure BDA00034581849300000717
Figure BDA0003458184930000081
Figure BDA0003458184930000082
wherein,
Figure BDA0003458184930000083
and
Figure BDA0003458184930000084
respectively adopting the traffic volume of a road, a railway, an aviation and a water transportation mode between a traffic area i and a traffic area j;
step D2, carrying out the traffic volume search in a manner of division, and using Excel, Matlab and other software;
the road mode is as follows: the data collected in the step A) between the traffic area i and the traffic area j are sequentially searched, and when the data exist
Figure BDA0003458184930000085
And is
Figure BDA0003458184930000086
And is provided with
Figure BDA0003458184930000087
At this time, will
Figure BDA0003458184930000088
Is directly added to
Figure BDA0003458184930000089
The above step (1);
the railway mode is as follows: the data collected in the step A) between the traffic area i and the traffic area j are searched in sequence, and when the data exist
Figure BDA00034581849300000810
And is
Figure BDA00034581849300000811
And is
Figure BDA00034581849300000812
At this time, will
Figure BDA00034581849300000813
Is directly added to
Figure BDA00034581849300000814
The above step (1);
an aviation mode: the data collected in the step A) between the traffic area i and the traffic area j are sequentially searched, and when the data exist
Figure BDA00034581849300000815
And is
Figure BDA00034581849300000816
And is
Figure BDA00034581849300000817
At this time, will
Figure BDA00034581849300000818
Is directly added to
Figure BDA00034581849300000819
The above step (1);
water transportation mode: the data collected in the step A) between the traffic area i and the traffic area j are sequentially searched, and when the data exist
Figure BDA00034581849300000820
And is provided with
Figure BDA00034581849300000821
And is
Figure BDA00034581849300000822
At this time, will
Figure BDA00034581849300000823
Is directly added to
Figure BDA00034581849300000824
C, removing;
wherein p and q are respectively the serial numbers of the traffic areas, both p and q are integers larger than 0, and p belongs to n, and q belongs to n;
Figure BDA00034581849300000825
a traffic area serial number for transfer of the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area p to the traffic area q;
Figure BDA00034581849300000826
the travel mode is adopted in the mth travel mode combination from the traffic area p to the traffic area q;
Figure BDA00034581849300000827
the trip proportion of the kth feasible trip mode combination between the traffic area p and the traffic area q; g is a radical of formulap,qThe travel demand from the traffic area p to the traffic area q;
step D3, performing mode OD result arrangement: and D2, sorting the results of the sub-mode row amount search in the step D2 to obtain a sub-mode OD matrix, wherein the specific results are as follows:
Figure BDA0003458184930000091
Figure BDA0003458184930000092
Figure BDA0003458184930000093
Figure BDA0003458184930000101
the examples described herein are merely illustrative of the preferred embodiments of the present invention and do not limit the spirit and scope of the present invention, and various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the design concept of the present invention shall fall within the protection scope of the present invention.

Claims (7)

1. A comprehensive traffic distribution mode OD obtaining method considering trip travel is characterized by comprising the following steps:
step A, data acquisition: collecting travel data of n traffic areas within the area needing to be analyzed;
b, utility calculation: b, calculating the travel utility of all feasible travel mode combinations between the traffic area i and the traffic area j according to the data collected in the step A;
step C, proportion analysis: calculating the travel proportion of all feasible travel mode combinations between the traffic area i and the traffic area j by adopting the travel utility calculated in the step B;
step D, OD obtains: and D, combining the data acquired in the step A and the travel proportion calculated in the step C, and calculating to obtain a sub-mode OD matrix of the travel modes between the traffic area i and the traffic area j.
2. The method for acquiring the OD of the comprehensive traffic separation mode considering the trip travel according to claim 1, wherein the step A specifically comprises the following steps:
collecting travel OD matrixes in the region needing analysis:
Figure FDA0003458184920000011
wherein, gi,jThe travel demand from a traffic area i to a traffic area j, n is the total number of the traffic areas in the area range needing to be analyzed, i and j are bothIs an integer greater than 0, and i belongs to n, and j belongs to n;
collecting the number N of feasible travel mode combinations between a traffic area i and a traffic area ji,j
Collecting the accumulated quantity of travel modes adopted in the kth feasible travel mode combination from the traffic area i to the traffic area j
Figure FDA0003458184920000012
Collecting the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure FDA0003458184920000013
Collecting travel distance adopted by mth type in kth feasible travel mode combination between traffic area i and traffic area j
Figure FDA0003458184920000014
Collecting traffic area serial numbers transferred by the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area i to the traffic area j
Figure FDA0003458184920000015
Wherein k is an integer greater than 0 and k is equal to or less than Nij(ii) a m is an integer greater than 0, and
Figure FDA0003458184920000016
Figure FDA0003458184920000017
the values are 1, 2, 3 and 4, which respectively represent highway, railway, aviation and water transportation travel modes;
Figure FDA0003458184920000018
the unit is kilometer;
Figure FDA0003458184920000019
is an integer greater than 0, and
Figure FDA00034581849200000110
Figure FDA00034581849200000111
indicating that the endpoint is not to be changed; travel modes include highways, railways, aviation and water transportation.
3. The method for obtaining the comprehensive traffic distribution mode OD considering the trip travel according to claim 2, wherein in the step B, the travel utility of the kth feasible travel mode combination between the traffic zone i and the traffic zone j is calculated by adopting the following formula
Figure FDA0003458184920000021
Figure FDA0003458184920000022
Wherein,
Figure FDA0003458184920000023
for distance utility function, representation is taken
Figure FDA0003458184920000024
Travel mode trip
Figure FDA0003458184920000025
Trip utility of distance;
Figure FDA0003458184920000026
to transfer the utility function, express from
Figure FDA0003458184920000027
Travel mode is transferred to
Figure FDA0003458184920000028
Transfer utility of travel patterns.
4. The method for obtaining the OD of the comprehensive transportation mode considering the trip according to claim 3, wherein in the step C, the trip proportion of the kth feasible trip mode combination from the transportation area i to the transportation area j is
Figure FDA0003458184920000029
Calculated using the formula:
Figure FDA00034581849200000210
wherein e is a natural base number, o is 1 or more and N or lessi,jThe number of the integer (c) of (d),
Figure FDA00034581849200000211
indicated as the o-th feasible travel pattern combination between traffic zone i and traffic zone j.
5. The method for acquiring the OD in the comprehensive traffic mode considering the trip travel according to claim 4, wherein the step D specifically comprises the following steps:
step D1, initializing the sub-mode OD matrix: initializing the sub-mode OD matrix of the highway, the railway, the aviation and the water transportation, and dividing the highway into sub-modes OD1Matrix, railway mode OD2Matrix and aviation separation mode OD3Matrix and water movement mode OD4All elements in the matrix are set to 0, wherein,
Figure FDA00034581849200000212
Figure FDA00034581849200000213
Figure FDA0003458184920000031
Figure FDA0003458184920000032
Figure FDA0003458184920000033
and
Figure FDA0003458184920000034
respectively adopting the traffic volume of a road, a railway, an aviation and a water transportation mode between a traffic area i and a traffic area j;
step D2, performing load search in different modes:
the road mode is as follows: for the area from the traffic area i to the traffic area j, the data acquired in the step A are sequentially searched, and when the data are searched, the data are transmitted to the traffic area j
Figure FDA0003458184920000035
And is
Figure FDA0003458184920000036
And is
Figure FDA0003458184920000037
Will be provided with
Figure FDA0003458184920000038
Is directly added to
Figure FDA0003458184920000039
C, removing;
the railway mode is as follows: the data collected in the step A are searched in sequence from the traffic area i to the traffic area j, and when the data are searched in sequence, the data are transmitted to the traffic area j
Figure FDA00034581849200000310
And is
Figure FDA00034581849200000311
And is
Figure FDA00034581849200000312
Will be provided with
Figure FDA00034581849200000313
Is accumulated to
Figure FDA00034581849200000314
The above step (1);
an aviation mode: the data collected in the step A) between the traffic areas i and j are searched in sequence when
Figure FDA00034581849200000315
And is
Figure FDA00034581849200000316
And is
Figure FDA00034581849200000317
Will be provided with
Figure FDA00034581849200000318
Is accumulated to
Figure FDA00034581849200000319
The above step (1);
water transportation mode: the data collected in the step A) between the traffic areas i and j are searched in sequence when
Figure FDA00034581849200000320
And is
Figure FDA00034581849200000321
And is
Figure FDA00034581849200000322
Will be provided with
Figure FDA00034581849200000323
Is accumulated to
Figure FDA00034581849200000324
The above step (1);
wherein p and q are respectively the serial numbers of the traffic areas, both p and q are integers larger than 0, and p belongs to n, and q belongs to n;
Figure FDA00034581849200000325
a traffic area serial number for transfer of the trip mode adopted by the mth in the kth feasible trip mode combination from the traffic area p to the traffic area q;
Figure FDA00034581849200000326
the travel mode is adopted in the mth travel mode combination from the traffic area p to the traffic area q;
Figure FDA00034581849200000327
the travel proportion of the kth feasible travel mode combination between the traffic area p and the traffic area q; gp,qThe travel demands from the traffic area p to the traffic area q;
step D3, performing mode OD result arrangement: and D2, sorting the results of the sub-mode column size search in the step D2 to obtain a sub-mode OD matrix.
6. The method for obtaining the comprehensive traffic distribution mode OD considering the trip travel according to claim 2, wherein in step A, the cumulative number of travel modes adopted in the kth feasible travel mode combination from the traffic zone i to the traffic zone j
Figure FDA0003458184920000041
To pair
Figure FDA0003458184920000042
Counting, if the mode transfer occurs in the traffic area, not counting the travel mode conversion in the traffic area, only counting the travel mode leaving the traffic area at last
Figure FDA0003458184920000043
In (1).
7. The method for obtaining the OD of the comprehensive transportation modes considering the trip, according to claim 6, wherein in step A, the cumulative number of the trip modes adopted in the kth feasible trip mode combination from the transportation area i to the transportation area j
Figure FDA0003458184920000044
To pair
Figure FDA0003458184920000045
Counting, if the same trip mode appears more than once in the feasible trip mode combination, counting according to the times of the appearance
Figure FDA0003458184920000046
In (1).
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080312811A1 (en) * 2007-06-15 2008-12-18 Xanavi Informatics Corporation Traffic information providing system and method for generating traffic information
CN109034506A (en) * 2018-09-18 2018-12-18 中铁第五勘察设计院集团有限公司 A kind of comprehensive passenger transport hub through transport traffic passenger flow forecast method
CN109558978A (en) * 2018-11-26 2019-04-02 东南大学 Regional traffic model split method based on trip distance

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080312811A1 (en) * 2007-06-15 2008-12-18 Xanavi Informatics Corporation Traffic information providing system and method for generating traffic information
CN109034506A (en) * 2018-09-18 2018-12-18 中铁第五勘察设计院集团有限公司 A kind of comprehensive passenger transport hub through transport traffic passenger flow forecast method
CN109558978A (en) * 2018-11-26 2019-04-02 东南大学 Regional traffic model split method based on trip distance

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
XUEYAN WEI 等: "Optimization and Comparative Analysis of Traffic Restriction Policy by Jointly Considering Carpool Exemptions", SUSTAINABILITY, 18 September 2020 (2020-09-18), pages 1 - 15 *
刘丽华 等: "城市交通需求预测理论与模型研究综述", 科学技术与工程, vol. 21, no. 30, 31 December 2021 (2021-12-31), pages 1 - 10 *

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