Travel generation method under multi-dimensional space constraint

Abstract

The invention discloses a travel generation method under multi-dimensional space constraint, and belongs to the technical field of traffic simulation. In order to effectively cope with the demand generated by urban travel, the method comprises the following steps: establishing a population number set under different travel zones, different groups and different travel purposes based on travel zones and travel purposes; calculating the travel rates of the different travel zones, different groups and different travel purposes; performing statistics to obtain a total travel amount set of the sub-travel zones of the mobile phone signaling data and a total travel amount set of the sub-travel purposes of the mobile phone signaling data; calculating the travel volume under different regions, different crowds and different purposes, and then constructing an initial travel matrix; constructing a total travel amount comparison equation under the travel purpose and performing comparison; constructing a travel total amount comparison equation of the travel zone and performing comparison; and if the travel total amount comparison equation of the travel zone is met, outputting a current travel amount matrix, and if the travel total amount comparison equation is not met, calculating an adjustment coefficient of the travel zone and updating the travel matrix. According to the method, travel generation of different crowds is obtained under the multi-dimensional space constraint.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic simulation, and particularly relates to a travel generation method under multi-dimensional space constraints. Background Art

[0002] Currently, in the field of traffic models, the travel rates of different populations are usually obtained through household travel surveys. However, household surveys are costly, and data acquisition is quite challenging. In particular, the interval of household travel surveys is relatively long, and the lack of up-to-date survey data makes it extremely difficult to obtain the latest travel patterns of different populations in traffic model construction. Summary of the Invention

[0003] The problem to be solved by the present invention is to effectively meet the demand for urban travel generation, and a travel generation method under multi-dimensional space constraints is proposed.

[0004] To achieve the above object, the present invention is realized through the following technical solutions:

[0005] A travel generation method under multi-dimensional space constraints, comprising the following steps:

[0006] S1. Based on a city or region, divide the travel zones of the traffic model to obtain a set of travel zones;

[0007] S2. Collect the travel purposes of the traffic model to obtain a set of travel purposes;

[0008] S3. Collect the types of resident populations of the traffic model to obtain a set of population groups, and then perform cross-classification based on the travel zones obtained in step S1 and the travel purposes obtained in step S2 to establish a set of population numbers under different travel zones, different populations, and different travel purposes;

[0009] S4. Collect the historical household travel survey data, calculate the travel rates under different travel zones, different populations, and different travel purposes to obtain a set of travel rates;

[0010] S5. Collect mobile signaling data, and then statistically obtain a set of total travel amounts by travel zone of the mobile signaling data and a set of total travel amounts by travel purpose of the mobile signaling data;

[0011] S6. Calculate the travel amounts under different zones, different populations, and different purposes, and then construct an initial travel matrix. Sum the elements of each row and each column of the initial travel matrix. The sum of the columns of the initial travel matrix is the total travel amount for each type of travel purpose, and the sum of the rows of the initial travel matrix is the total travel amount by zone and population;

[0012] S7. Construct a comparison equation for the total travel volume under the travel purpose, compare the total travel volume obtained for each travel purpose with the total travel volume by travel purpose of the mobile phone signaling data obtained in step S5. If the comparison equation for the total travel volume under the travel purpose is satisfied, output the current travel volume matrix. If the comparison equation for the total travel volume is not satisfied, calculate the adjustment coefficient under the travel purpose, then update the travel rate obtained from the historical resident travel survey data based on the adjustment coefficient under the travel purpose to obtain an updated set of travel rates, and update the travel matrix to obtain an updated travel matrix;

[0013] S8. Construct a comparison equation for the total travel volume of the travel zone. Based on the updated travel matrix obtained in step S7, sum each row and each column of the updated travel matrix, then sum the row sum results according to the travel zone to calculate the total travel volume under each travel zone. Then compare the total travel volume under each travel zone with the total travel volume by travel zone of the mobile phone signaling data obtained in step S5. If the comparison equation for the total travel volume of the travel zone is satisfied, output the current travel volume matrix. If the comparison equation for the total travel volume is not satisfied, calculate the adjustment coefficient of the travel zone, then update the travel rate obtained from the historical resident travel survey data based on the adjustment coefficient of the travel zone to obtain a re-updated set of travel rates, and update the travel matrix to obtain a re-updated travel matrix;

[0014] S9. Repeat steps S7 and S8 for the re-updated travel matrix obtained in step S8 until the loop ends.

[0015] Further, in step S1, the travel zone set is denoted as B ∈ (b 1 , b 2 , …, b n ), where b 1 is zone 1, b 2 is zone 2, and b n is zone n.

[0016] Further, in step S2, the travel purpose set is denoted as A ∈ (a 1 , a 2 , …, a t ), where a 1 is travel purpose 1, a 2 is travel purpose 2, and a t is travel purpose t.

[0017] Further, in step S3, the population grouping set is denoted as P ∈ (p 1 , p 2 , …, p m ), where p 1 is population 1, p 2 is population 2, and p mFor population m;

[0018] The set of population numbers by travel zone, population, and travel purpose is denoted as Among them, is the number of trips for zone n, population m, and travel purpose t. The set of population numbers by travel zone, population, and travel purpose is a three-dimensional matrix.

[0019] Furthermore, the travel rate set in step S4 is denoted as Among them, is the travel rate for zone n, population m, and travel purpose t.

[0020] Furthermore, the set of total travel amounts by travel zone for mobile signaling data in step S5 is denoted as QB ∈ (qb 1 , qb 2 , …, qb n ), where qb n is the total travel amount for zone n of mobile signaling data; the set of total travel amounts by travel purpose for mobile signaling data is denoted as QA ∈ (qa 1 , qa 2 , …, qa t ), where qa t is the total travel amount for travel purpose t of mobile signaling data.

[0021] Furthermore, the formula for calculating the travel volume by zone, population, and purpose in step S6 is:

[0022]

[0023] Among them, is the travel volume for travel zone i, population k, and travel purpose j; is the number of trips for travel zone i, population k, and travel purpose j; is the travel rate for travel zone i, population k, and travel purpose j, where i ∈ (1, 2, …, n), k ∈ (1, 2, …, m), and j ∈ (1, 2, …, t).

[0024] Furthermore, the specific implementation method of step S7 includes the following steps:

[0025] S7.1. Construct a comparison equation for the total travel amount by travel purpose, and the expression is:

[0026]

[0027] Among them, is the total travel amount for travel purpose j calculated from the initial travel matrix, and qa j is the total travel amount for travel purpose j obtained from mobile signaling data;

[0028] S7.2. Compare the total travel volume under each obtained travel purpose with the total travel volume under the travel purpose in the mobile signaling data obtained in step S5. If the total travel volume comparison equation under the travel purpose is satisfied, output the current travel volume matrix. If the total travel volume comparison equation is not satisfied, calculate the adjustment coefficient under the travel purpose, and the expression is:

[0029]

[0030] where α j is the adjustment coefficient of the travel rate of the population in each zone under travel purpose j;

[0031] S7.3. Then update the travel rate obtained from the resident travel history survey data based on the adjustment coefficient under the travel purpose, and the expression is:

[0032]

[0033] where is the adjusted travel rate for travel zone i, population k, and travel purpose j;

[0034] S7.4. Update the travel rate set and update the travel matrix to obtain the updated travel matrix, and the updated travel rate set

[0035] Furthermore, the specific implementation method of step S8 includes the following steps:

[0036] S8.1. Based on the updated travel matrix obtained in step S7, sum each row and each column of the updated travel matrix, and then sum the row sum results according to the travel zone to obtain the total travel volume under each travel zone, and the expression is:

[0037]

[0038] where ∑Q i′ is the total travel volume of travel zone i in the updated travel matrix, is the travel volume of travel zone i, population k, and purpose j in the updated travel matrix;

[0039] S8.2. Construct the total travel volume comparison equation for the travel zone, and the expression is:

[0040]

[0041] where qb i is the total travel volume of travel zone i obtained from the mobile signaling data;

[0042] S8.3. Compare the total travel volume under each travel zone with the total travel volume by travel zone of the mobile signaling data obtained in step S5. If the total travel volume comparison equation of the travel zone is satisfied, output the current travel volume matrix; if the total travel volume comparison equation is not satisfied, calculate the adjustment coefficient β of the travel zone i , and the expression is:

[0043]

[0044] S8.4. Then update the travel rate obtained from the resident travel history survey data based on the adjustment coefficient of the travel zone. The expression is:

[0045]

[0046] where is the travel rate after re-adjustment for travel zone i, population k, and travel purpose j;

[0047] S8.5. Update the travel rate set and the travel matrix again to obtain the travel matrix after re-update and the travel rate matrix after re-adjustment

[0048] Advantages of the present invention:

[0049] The travel generation method under multi-dimensional space constraints described in the present invention is carried out under the multi-dimensional space constraint conditions based on historical survey data and mobile signaling data. This method is applicable to the situation where the urban population structure has not changed significantly since the last historical resident travel survey, and can effectively meet the demand for urban travel generation. By comprehensively using historical survey data and mobile signaling data, this method obtains the travel generation of different populations under multi-dimensional space constraints

[0050] The travel generation method under multi-dimensional space constraints described in the present invention iteratively updates the generation rate adjustment coefficient by comparing the differences between the target value and the actual value, so that the travel volume under each purpose and each travel zone is closer to the given target value, and convergence is achieved under multi-dimensional space constraint conditions. This method can effectively solve the problem of the travel distribution ratio of different zones, different purposes, and different populations in the absence of the latest travel survey data Description of the Drawings

[0051] Figure 1 is the travel generation calculation flow chart of the present invention Detailed Embodiments

[0052] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the specific embodiments described are only a part of the embodiments of the present invention, rather than all of the specific embodiments. Usually, the components of the specific embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0053] Therefore, the following detailed description of the specific embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected specific embodiments of the present invention. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0054] To further understand the content, features and effects of the present invention, the following specific embodiments are exemplified and described in detail in conjunction with the attached Figure 1 as follows:

[0055] Example 1:

[0056] A travel generation method under multi-dimensional space constraints includes the following steps:

[0057] S1. Based on a city or region, divide the travel zones of the traffic model to obtain a set of travel zones;

[0058] Further, in step S1, the set of travel zones is denoted as B ∈ (b 1 , b 2 , …, b n ), where b 1 is zone 1, b 2 is zone 2, and b n is zone n;

[0059] Further, in the process of constructing a traffic model of a city or a region, due to the influence of the spatial location, group division and geographical separation of the city or region, there are large differences in the development levels of each zone. In order to improve the accuracy of the traffic model, when constructing the traffic model, it is usually considered from the perspectives of traffic demand characteristics, regional development level, etc., and the research scope is divided into several model zones. The development degrees and travel characteristics within the same zone are similar, while the travel characteristics of different zones are quite different. The division of model zones is mainly for the calculation of travel generation rates and the statistics of model travel volumes.

[0060] S2. Collect the travel purposes of the traffic model to obtain a set of travel purposes;

[0061] Further, the set of travel purposes in step S2 is denoted as A ∈ (a 1 , a 2 , …, a t ), where a 1 is the travel purpose 1, a 2 is the travel purpose 2, a t is the travel purpose t.

[0062] Further, the travel purposes of the traffic model can be subdivided according to the attributes of the departure place and different travel purposes. For example: work trips based on home, school trips based on home, other trips based on home, work trips not based on home, etc.

[0063] S3. Collect the types of resident populations of the traffic model to obtain a set of population groups, and then conduct cross-classification based on the travel zones obtained in step S1 and the travel purposes obtained in step S2 to establish a set of population quantities under different travel zones, different populations, and different travel purposes;

[0064] Further, the set of population groups in step S3 is denoted as P ∈ (p 1 , p 2 , …, p m ), where p 1 is population 1, p 2 is population 2, p m is population m;

[0065] The set of population quantities under different travel zones, different populations, and different travel purposes is denoted as Among them, is the number of trips under zone n, population m, and travel purpose t, and the set of population quantities under different travel zones, different populations, and different travel purposes is a three-dimensional matrix.

[0066] Further, in the traffic model, the types of populations are generally divided into permanent residents, temporary residents, and floating populations, and population data can be obtained from the local statistical bureau and public security bureau. Considering the differences in population occupations, incomes, car ownership situations, travel modes, and travel rates, the populations are grouped.

[0067] S4. Collect the historical survey data of residents' trips, calculate the travel rates under different travel zones, different populations, and different travel purposes, and obtain a set of travel rates;

[0068] Further, the set of travel rates in step S4 is denoted as Among them, is the travel rate under zone n, population m, and travel purpose t;

[0069] Furthermore, the resident travel survey data includes personal attributes of residents such as personal occupation and gender, family attributes such as car ownership and income, and resident travel characteristics. Based on the historical data of the resident travel survey, the travel rates of different people in different zones for different travel purposes can be calculated.

[0070] S5. Collect mobile phone signaling data, and then statistically obtain the travel total amount set by travel zone of the mobile phone signaling data and the travel total amount set by travel purpose of the mobile phone signaling data;

[0071] Furthermore, the travel total amount set by travel zone of the mobile phone signaling data in step S5 is denoted as QB ∈ (qb 1 , qb 2 , …, qb n ), where qb n is the travel total amount of zone n of the mobile phone signaling data; the travel total amount set by travel purpose of the mobile phone signaling data is denoted as QA ∈ (qa 1 , qa 2 , …, qa t ), where qa t is the travel total amount under travel purpose t of the mobile phone signaling data;

[0072] Furthermore, the mobile phone signaling data has the characteristics of being easy to obtain and having a small granularity, and is currently commonly used in traffic model construction. The travel data of mobile phone signaling is generally at the grid level, and the travel total amount by zone and the travel total amount by purpose can be statistically obtained according to the construction requirements of the model.

[0073] S6. Calculate the travel volume by zone, population, and purpose, and then construct an initial travel matrix. Sum each row and each column of the initial travel matrix. The column sum result of the initial travel matrix is the travel total amount for each type of travel purpose, and the row sum result of the initial travel matrix is the travel total amount by zone and population;

[0074] Furthermore, the formula for calculating the travel volume by zone, population, and purpose in step S6 is:

[0075]

[0076] Among them, is the travel volume of travel zone i, population k, and travel purpose j; is the number of travel people of travel zone i, population k, and travel purpose j; is the travel rate of travel zone i, population k, and travel purpose j, where i ∈ (1, 2, …, n), k ∈ (1, 2, …, m), j ∈ (1, 2, …, t).

[0077] Furthermore, the initial travel matrix is shown in Table 1:

[0078] Table 1 Initial Trip Matrix

[0079]

[0080] S7. Construct a comparison equation for the total trip volume under the trip purpose, compare the total trip volume obtained for each type of trip purpose with the total trip volume by trip purpose of the mobile phone signaling data obtained in step S5. If the comparison equation for the total trip volume under the trip purpose is satisfied, output the current trip volume matrix. If the comparison equation for the total trip volume is not satisfied, calculate the adjustment coefficient under the trip purpose, then update the trip rate obtained from the historical resident travel survey data based on the adjustment coefficient under the trip purpose to obtain an updated set of trip rates, and update the trip matrix to obtain an updated trip matrix;

[0081] Further, the specific implementation method of step S7 includes the following steps:

[0082] S7.1. Construct a comparison equation for the total trip volume under the trip purpose, and the expression is:

[0083]

[0084] Among them, is the total trip volume for purpose j calculated from the initial trip matrix, and qa j is the total trip volume for trip purpose j obtained from the mobile phone signaling data;

[0085] S7.2. Compare the total trip volume obtained for each type of trip purpose with the total trip volume by trip purpose of the mobile phone signaling data obtained in step S5. If the comparison equation for the total trip volume under the trip purpose is satisfied, output the current trip volume matrix. If the comparison equation for the total trip volume is not satisfied, calculate the adjustment coefficient under the trip purpose, and the expression is:

[0086]

[0087] Among them, α j is the adjustment coefficient of the trip rate of the population in each zone under trip purpose j;

[0088] S7.3. Then update the trip rate obtained from the historical resident travel survey data based on the adjustment coefficient under the trip purpose, and the expression is:

[0089]

[0090] Among them, is the adjusted trip rate for travel zone i, population k, and trip purpose j;

[0091] S7.4. Update the set of trip rates and update the trip matrix to obtain an updated trip matrix, and the updated set of trip rates

[0092] Furthermore, the updated travel matrix is shown in Table 2:

[0093] Table 2 Updated travel matrix

[0094]

[0095]

[0096] S8. Construct a travel volume comparison equation for the travel zones. Based on the updated travel matrix obtained in step S7, sum each row and each column of the updated travel matrix, then sum the row summation results according to the travel zones to obtain the total travel volume under each travel zone. Then, compare the total travel volume under each travel zone with the total travel volume by travel zone of the mobile signaling data obtained in step S5. If the travel volume comparison equation for the travel zones is satisfied, output the current travel volume matrix. If the travel volume comparison equation is not satisfied, calculate the adjustment coefficient for the travel zones, then update the travel rate obtained from the resident travel history survey data based on the adjustment coefficient of the travel zones to obtain a newly updated set of travel rates, and update the travel matrix to obtain a newly updated travel matrix;

[0097] Furthermore, the specific implementation method of step S8 includes the following steps:

[0098] S8.1. Based on the updated travel matrix obtained in step S7, sum each row and each column of the updated travel matrix, then sum the row summation results according to the travel zones to obtain the total travel volume under each travel zone. The expression is:

[0099]

[0100] Among them, ∑Q i′ is the total travel volume of travel zone i of the updated travel matrix, is the travel volume of travel zone i, population k, and purpose j of the updated travel matrix;

[0101] S8.2. Construct a travel volume comparison equation for the travel zones. The expression is:

[0102]

[0103] Among them, qb i is the total travel volume of travel zone i obtained from the mobile signaling data;

[0104] S8.3. Compare the total travel volume in each travel zone with the total travel volume by travel zone obtained from the mobile signaling data in step S5. If the total travel volume comparison equation for the travel zone is satisfied, output the current travel volume matrix. If the total travel volume comparison equation is not satisfied, calculate the adjustment coefficient β of the travel zone i , and the expression is:

[0105]

[0106] S8.4. Then update the travel rate obtained from the resident travel history survey data based on the adjustment coefficient of the travel zone. The expression is:

[0107]

[0108] where is the travel rate after re-adjustment for travel zone i, population k, and travel purpose j;

[0109] S8.5. Update the travel rate set and the travel matrix again to obtain the travel matrix after re-update and the travel rate matrix after re-adjustment

[0110] S9. Repeat steps S7 and S8 for the travel matrix after re-update obtained in step S8 until the loop ends.

[0111] It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0112] Although the present application has been described above with reference to specific embodiments, various improvements can be made thereto and components thereof can be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in the present application can be combined with each other in any way, and the exhaustive description of these combinations is not given in this specification only for the consideration of saving space and resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A travel generation method under multidimensional space constraints, characterized in that: The steps include: S1. Divide the travel zones of the traffic model based on cities or regions to obtain a set of travel zones; S2. Collect the travel purpose of the traffic model to obtain a travel purpose set; S3. Collect the types of residents in the traffic model to obtain a set of population groups, and then cross-classify based on the travel zone obtained in step S1 and the travel purpose obtained in step S2 to establish a population set divided by travel zone, group and travel purpose; S4. Collect historical survey data on residents' travel, calculate the travel rates of different travel zones, different groups of people and different travel purposes, and obtain a set of travel rates; S5. Collecting mobile signaling data, and then statistically obtaining a total set of travel by travel zone and a total set of travel by travel destination by mobile signaling data; S6. Calculate the travel volume for different regions, different groups of people and different purposes, then construct an initial travel matrix, sum each row and each column of the initial travel matrix, and obtain the column sum of the initial travel matrix as the total travel volume for each type of travel purpose, and the row sum of the initial travel matrix as the total travel volume for different regions and different groups of people; S7. Construct a travel volume comparison equation under travel purpose, compare the obtained travel volume under each type of travel purpose with the travel volume under the divided travel purpose of the mobile phone signaling data obtained in step S5, if the travel volume comparison equation under the travel purpose is satisfied, output the current travel volume matrix, if the travel volume comparison equation under the travel purpose is not satisfied, calculate the adjustment coefficient under the travel purpose, and then update the travel rate obtained from the residents' travel history survey data based on the adjustment coefficient under the travel purpose to obtain an updated travel rate set, and update the travel matrix to obtain an updated travel matrix; S8. Construct a travel volume comparison equation for the travel zone. Based on the updated travel matrix obtained in step S7, sum each row and column of the updated travel matrix, and then sum the row summation results according to the travel zone to obtain the total travel volume in each travel zone. Then compare the total travel volume in each travel zone with the total travel volume of the travel zone of the mobile phone signaling data obtained in step S5. If the travel volume comparison equation for the travel zone is satisfied, output the current travel volume matrix. If the travel volume comparison equation is not satisfied, calculate the adjustment coefficient of the travel zone. Then, based on the adjustment coefficient of the travel zone, update the travel rate obtained from the residents' travel history survey data to obtain a travel rate set that is updated again. Then update the travel matrix to obtain the updated travel matrix. S9. Repeat steps S7 and S8 for the updated travel matrix obtained in step S8 until the loop ends.

2. The method for generating a trip under multidimensional space constraints according to claim 1, characterized in that: The travel zone set in step S1 is recorded as B∈(b1,b2,…,b n ), where b1 is zone 1, b2 is zone 2, and b n For zone n.

3. The method for generating a trip under multidimensional space constraints according to claim 2, characterized in that: The travel destination set in step S2 is recorded as A∈(a1,a2,…,a t ), where a1 is the travel purpose 1, a2 is the travel purpose 2, and a t For travel purposes.

4. The method for generating a trip under multidimensional space constraints according to claim 3, characterized in that: In step S3, the crowd grouping set is recorded as P∈(p1,p2,…,p m ), where p1 is population 1, p2 is population 2, and p m For the crowd m; The population quantity under the travel zone, group and travel purpose is recorded as in, is the number of travelers under zone n, group m, and travel purpose t. The set of population numbers divided by travel zone, group m, and travel purpose is a three-dimensional matrix.

5. The method for generating travel under multidimensional space constraints according to claim 4, characterized in that: The travel rate set in step S4 is recorded as in, is the travel rate for zone n, group m, and travel purpose t.

6. The method for generating a trip under multidimensional space constraints according to claim 5, characterized in that: The total travel volume set of the divided travel zones of the mobile phone signaling data in step S5 is recorded as QB∈(qb1,qb2,…,qb n ), qb n is the total number of trips in zone n of mobile phone signaling data; The total amount of travel under the travel purpose of mobile phone signaling data is recorded as QA∈(qa1,qa2,…,qa t ), qa t It is the total number of trips with travel purpose t from mobile phone signaling data.

7. The method for generating a trip under multidimensional space constraints according to claim 5, characterized in that: The formula for calculating the travel volume by region, population and purpose in step S6 is: in, is the travel volume of travel zone i, group k, and travel purpose j; is the number of travelers in travel zone i, group k, and travel purpose j; is the travel rate of travel zone i, group k, and travel purpose j, i∈(1,2,…,n), k∈(1,2,…,m), j∈(1,2,…,t).

8. The method for generating a trip under multidimensional space constraints according to claim 7, characterized in that: The specific implementation method of step S7 includes the following steps: S7.

1. Construct a comparison equation for the total amount of travel under travel purpose, expressed as: in, The total amount of trips to destination j is calculated for the initial trip matrix, qa j is the total number of trips with travel purpose j obtained from mobile phone signaling data; S7.

2. Compare the total amount of travel under each type of travel purpose obtained with the total amount of travel under the travel purpose obtained in the mobile phone signaling data in step S5. If the travel total amount comparison equation under the travel purpose is satisfied, the current travel volume matrix is ​​output. If the travel total amount comparison equation is not satisfied, the adjustment coefficient under the travel purpose is calculated, and the expression is: Among them, α j The adjustment coefficient for the travel rate of people in different places under travel purpose j; S7.

3. Then, the travel rate obtained from the historical survey data of residents’ travel is updated based on the adjustment coefficient under the travel purpose, and the expression is: in, is the adjusted travel rate for travel zone i, group k, and travel purpose j; S7.

4. Update the travel rate set and update the travel matrix to obtain the updated travel matrix and the updated travel rate set 9. The method for generating a trip under multidimensional space constraints according to claim 8, characterized in that: The specific implementation method of step S8 includes the following steps: S8.

1. Based on the updated travel matrix obtained in step S7, sum each row and column of the updated travel matrix, and sum the row sums according to the travel zones to obtain the total travel volume in each travel zone, which is expressed as: Among them, ∑Q i′ is the total travel volume of travel zone i in the updated travel matrix, is the travel volume of travel zone i, group k, and destination j in the updated travel matrix; S8.

2. Construct the travel volume comparison equation of the travel zone, which is expressed as: Among them, qb i is the total number of trips in travel zone i obtained from mobile phone signaling data; S8.

3. Compare the total amount of travel in each travel zone with the total amount of travel in the travel zone obtained from the mobile phone signaling data in step S5. If the travel total amount comparison equation of the travel zone is satisfied, output the current travel volume matrix. If the travel total amount comparison equation is not satisfied, calculate the adjustment coefficient β of the travel zone. i , the expression is: S8.

4. Then, the travel rate obtained from the historical survey data of residents’ travel is updated based on the adjustment coefficient of the travel zone, and the expression is: in, The travel rate after adjustment for travel zone i, group k, and travel purpose j; S8.

5. Update the travel rate set again and update the travel matrix to obtain the updated travel matrix and the adjusted travel rate matrix.

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