Comprehensive traffic transportation impedance modeling method

Abstract

The invention relates to a method for establishing a comprehensive transportation impedance model, and belongs to the technical field of transportation engineering and intelligent transportation technologies. The method comprises the following steps: respectively establishing time impedance models according to travel characteristics of road traffic, travel characteristics of railway traffic, travel characteristics of waterway traffic, travel characteristics of air traffic and hub transfer characteristics; and according to the road polynomial time impedance model, the common railway and high-speed railway construction time impedance model, the waterway transportation polynomial time impedance model, the air transportation time impedance model, the hub transfer time impedance model and a route selection model, comprehensive traffic distribution is carried out. The invention provides a simple and comparable traffic impedance model according to operation characteristics of five traffic modes. According to the method, the characteristics of each traffic transportation mode are integrated, the impedance of the transportation modes such as roads, railways, aviation and water transportation is considered, and the requirement of integrated analysis of the comprehensive traffic system is effectively met.

Description

Technical Field

[0001] The invention relates to a method for establishing a comprehensive transportation impedance model, and belongs to the technical field of transportation engineering and intelligent transportation technology. Background Art

[0002] Comprehensive transportation traffic impedance analysis is an important part of realizing integrated analysis of comprehensive transportation systems. The accuracy of impedance analysis of each mode has an important and even decisive impact on the calculation of transportation time and cost, traffic demand distribution analysis, traffic route selection and prediction, and integrated transportation flow distribution. Existing traffic impedance research is mainly carried out around road transportation. The research technology is relatively mature, and a series of classic models including the Federal Highway Administration model have been proposed. However, there are few impedance studies involving transportation modes such as railways, aviation, water transportation, and pipelines, which cannot effectively support the needs of integrated analysis of comprehensive transportation systems. Specifically, it is manifested in the following aspects:

[0003] ① Lack of analysis on bottleneck capacity and node delays of railway, aviation, water transport and other modes of transportation, making it impossible to accurately deduce the evolution of transportation time for each mode;

[0004] ② There is a lack of analysis of the impedance factors such as the convenience, comfort, and safety of each mode of transportation, which cannot fully reflect the differences in the mode choices of travelers;

[0005] ③ There is a lack of research on the impedance of comprehensive transportation hubs, which makes it impossible to effectively analyze the impact of mode conversion on passenger and freight transportation. Summary of the invention

[0006] Purpose of the invention: In view of the above shortcomings, the present invention discloses a method for calculating comprehensive transportation impedance modeling, breaking through the technical bottleneck of impedance analysis and modeling of various modes, and systematically solving the problems commonly existing in current impedance research, such as unclear transportation characteristics of various modes, inconsistent calibration of model parameters, and poor applicability.

[0007] The present invention adopts the following technical solution:

[0008] A method for comprehensive transportation impedance modeling, which establishes time impedance models according to the travel characteristics of highway traffic, railway traffic, waterway traffic, aviation traffic, and hub transfer characteristics;

[0009] The travel characteristics of highway traffic include traffic data on highways of different grades, as well as flow, speed, and travel time data. Polynomial fitting is performed on three grades of roads through flow, speed, and travel time data to construct polynomial time impedance models for highways of different grades.

[0010] Railway transportation includes conventional railways and high-speed railways. The characteristics of railway transportation include departure time, arrival time, departure station, arrival station, train type, train number, and fare data. Time impedance models are constructed for conventional railways and high-speed railways respectively.

[0011] The travel characteristics of waterway transportation are to extract AIS trajectory data from historical ship trajectory data as ship passage data; the sample unit is converted from ship trajectory points to ship navigation process, and a polynomial time impedance model for waterway transportation is constructed;

[0012] The travel characteristics of air traffic include flight and airport data, which are extracted and analyzed to construct an air transport time impedance model;

[0013] Hub transfer characteristics include hub inbound traffic and passenger arrival travel time data, and the data is extracted and analyzed to build a time impedance model for hub transfer;

[0014] Comprehensive traffic allocation is performed based on the highway polynomial time impedance model, conventional railway and high-speed railway construction time impedance model, water transport polynomial time impedance model, air transport time impedance model, hub transfer time impedance model and route selection model.

[0015] In the method for comprehensive transportation impedance modeling of the present invention, different levels of highways in the travel characteristics of highway traffic are divided into: expressways, provincial roads, and national roads; the steps for establishing the time impedance model are as follows:

[0016] (1.1) Collect traffic data on roads of different levels, and use drones to take aerial videos of typical highways, national roads, and provincial roads during peak / off-peak hours on weekdays to collect data;

[0017] (1.2) Extract relevant data on roads of different grades, identify and count the traffic of four types of vehicles, namely small vehicles, medium-sized vehicles, empty container trucks, and large vehicles, based on deep learning methods, and extract traffic data; use Tracker software to set the scale and reference system, select the target vehicle for automatic tracking, and extract the real-time speed; use the YOLOv4+deepsort target tracking algorithm, configure the target tracking model, and extract the travel time;

[0018] (1.3) Based on the data extracted in (1.2), analyze the operating characteristics of roads of different levels and obtain traffic data on typical highways, national highways, and provincial highways;

[0019] (1.4) Perform polynomial fitting on traffic data on typical highways, national roads, and provincial roads:

[0020] make:

[0021]

[0022] The fitting function is:

[0023] y=b1x+b2x 2 +b3x 3 +b4

[0024] Among them, t is the vehicle travel time; t0 is the free flow travel time; q is the traffic flow; c is the design capacity; b1, b2, b3, b4 are the parameters to be fitted;

[0025] Use relevant software to write a program, calibrate the above three models (expressway, national highway, provincial highway) according to the highway grade, and obtain relevant calibration parameters. The results are as follows:

[0026] The calibration parameters for expressways, national roads and provincial roads are as follows:

[0027] Highway: y h =-0.604x+12.50(x) 2 +16.23(x) 3 +2.133;

[0028] National Highway: -0.931x+4.719(x) 2 -3.513(x) 3 +1.411;

[0029] Dart: -2.249x+8.627(x) 2 -6.922(x) 3 +1.559.

[0030] The method for comprehensive transportation impedance modeling of the present invention includes the following steps for constructing the time impedance model of conventional railways and high-speed railways:

[0031] (2.1) Obtain data related to conventional and high-speed railways, and extract data such as departure time, arrival time, departure station, arrival station, train type, train number, and ticket price;

[0032] (2.2) Construct railway impedance function model:

[0033] T=αL+βN+c

[0034] Where: T is the section travel time; L is the section length; N is the number of stops in the section; α, β, c are parameters to be determined;

[0035] (2.3) Using the relevant data of conventional railways and high-speed railways, the impedance function model is calibrated to obtain the high-speed railway time impedance model and the conventional railway time impedance model;

[0036] Get the calibration results of high-speed rail time and ordinary rail time:

[0037] High-speed rail:

[0038] T=0.0031*L+0.2098*N+0.1731

[0039] Ordinary Railway:

[0040] T=0.0121*L+0.1980*N-0.0745

[0041] The method for comprehensive transportation impedance modeling of the present invention, the waterway transportation polynomial time impedance model is constructed as follows:

[0042] (3.1) Obtain ship historical trajectory data and waterway technical standard data, including ship type, position, speed, time, and waterway width information;

[0043] (3.2) Perform data screening. For missing data of some ships, classify them according to ship types, calculate the mean of length, width and draft data of different types of ships, and use it to fill the data;

[0044] (3.3) Taking the waterways within a specific range as the research object, we screened out the data that passed through the selected waterways for research, and counted the passage data of the researched waterways, that is, the distance and time of each ship passing through the waterway. We determined the distance that the ship passed by by accumulating the distance between the previous and next track points, and calculated the speed of the passing section based on the distance and passing time;

[0045] (3.4) Construct and calibrate the water transport impedance model;

[0046] (3.4.1) The BPR function is introduced into the water transport impedance modeling, and the maximum speed of all ships passing through the water transport section is selected as the free passing speed; the water transport capacity is calculated based on the maximum number of ships observed in the waterway; the water transport impedance model is:

[0047]

[0048] Where L is the length of the water transport section. In the water transport impedance study, q is the ship flow of the waterway section, C is the actual traffic capacity of the waterway section, L is the length of the waterway section, and v f The speed at which ships freely pass through the waterway section. Considering the differences between water transport and road transport in actual situations, the two parameters α and β need to be calibrated based on the data.

[0049] (3.4.2), the model is transformed as follows:

[0050]

[0051]

[0052] y = βx + lnα;

[0053] (3.4.3) To obtain a better fitting effect, the BPR polynomial regression model is constructed based on the above formula as follows:

[0054]

[0055] Where n is the degree of the polynomial;

[0056] (3.4.4) Parameter calibration is performed based on known data, and the definite parameters of water transport impedance are obtained as follows:

[0057]

[0058] (3.4.5) The water transport BPR model is transformed into a polynomial and the independent variables are upgraded to polynomial linear fitting. The fitting results are as follows.

[0059]

[0060] The method for comprehensive transportation impedance modeling of the present invention comprises the following steps for constructing an aviation transportation time impedance model:

[0061] (4.1) Obtain flight dynamic data and airport static data, including aircraft real-time position, speed, take-off and landing time, delay reasons, airport final approach, and runway number data;

[0062] (4.2) Preprocess the data and filter the flights between the airports under study; extract route characteristics including route length, flight speed, and route free flight time data.

[0063] Airport characteristics include data such as airport load factor and number of airport runways, and flight characteristics include data such as average travel time and take-off / landing delay time;

[0064] Departure flight delay time:

[0065]

[0066] Among them, T D Departure flight delay time, is the actual departure time of the flight, To plan the departure time;

[0067] The total travel time cost for a traveler taking a flight is:

[0068] T=t+T D

[0069] Among them, T is the total travel time cost of the traveler taking the flight, and t is the actual flight time of the flight;

[0070] (4.3) The following aviation impedance function model based on the landing airport runway load coefficient is constructed as follows:

[0071]

[0072] Where t is the actual flight time of the flight, that is, the time interval between the actual landing time and the actual take-off time of the flight; t0 is the free flow time of the flight; q d The flight flow at the landing airport; d Airport runway capacity for landing; is the landing airport runway load factor; α, β are model parameters;

[0073] Calibrate according to the parameters, the result is:

[0074]

[0075] (4.4) Construct the flight travel time to update the aviation impedance function model and calibrate it:

[0076] The take-off airport traffic saturation variable is further added to the model to improve the above model and refit the model; the updated aviation impedance function model expression is:

[0077]

[0078] In the formula, q o is the flight flow of the departure airport; c o is the runway capacity of the take-off airport; α, β, m, n are model parameters;

[0079] The updated calibration results of the aviation impedance function model are:

[0080]

[0081] The method for comprehensive transportation impedance modeling of the present invention constructs a time impedance model for hub transfer, and the steps are as follows:

[0082] (5.1) Obtain the minute-by-minute passenger flow in the hub, the length of time passengers depart in advance, and the travel time to the hub station;

[0083] (5.2) Based on the data obtained in (5.1), a linear model is used to express the relationship between the advance departure time and the inbound flow and travel time to construct a time impedance model for hub transfer, which is expressed as follows:

[0084] t A =a+bq+ct j

[0085] Among them, t A represents the length of time that passengers depart in advance; q represents the passenger flow when entering the station; t j represents the travel time of passengers arriving at the station; a, b, c are fitting parameters.

[0086] The calibration results are:

[0087] t A =48.68+0.036q+0.795t j .

[0088] In the method for comprehensive transportation impedance modeling of the present invention, the steps of step 6 are as follows:

[0089] (6.1) According to the above steps, the impedance model of five modes of transportation, namely road, rail, water, aviation, and hub transfer, is obtained, and the impedance characteristics of each mode of transportation are analyzed;

[0090] (6.2) Considering the impedance model and characteristics of each transportation mode, the route selection model is combined to carry out comprehensive traffic allocation. The integrated traffic allocation of the comprehensive transportation network adopts the improved Logit path selection model and node allocation algorithm.

[0091] (6.2.1) For the traffic volume w between the starting point O and the end point D ij First, we analyze the effective travel path from the starting point O to the end point D on the comprehensive transportation network.

[0092] (6.2.2) Using the traffic impedance function proposed above to analyze the comprehensive traffic impedance of each effective travel path, the improved Logit path selection model is proposed as follows:

[0093]

[0094] Where P(I,J,y) is w ij The allocation rate on the yth travel path, F y 、F U are the comprehensive traffic impedances of the yth and Uth travel routes respectively; is the average authority comprehensive traffic impedance of each travel path under all transportation modes; η is the traffic allocation parameter of the comprehensive transportation network; v is the number of effective travel routes in the comprehensive transportation network.

[0095] Where P(I,J,y) is w ij The allocation rate on the yth travel path, F y 、F U are the comprehensive transportation impedances of the yth and Uth travel routes, including the sum of the impedances of all transportation modes on the route;

[0096] The impedance of each mode of transportation is calculated by the time impedance model and calibration results of road transportation, railway transportation, water transportation, air transportation, and hub transfer;

[0097] F is the average comprehensive transportation impedance of each travel path under all transportation modes, which is calculated by the time impedance model and calibration results of road transportation, railway transportation, water transportation, air transportation, and hub transfer;

[0098] η is the traffic allocation parameter of the comprehensive transportation network; v is the number of effective travel routes in the comprehensive transportation network.

[0099] Beneficial Effects

[0100] The method for comprehensive transportation impedance modeling provided by the present invention has the following advantages:

[0101] 1. Existing research mainly focuses on the traffic impedance of highways, and less attention is paid to the impedance models of other traffic modes. Most models are mainly proposed for traffic operations rather than planning, and are often not comparable or have too high calculation costs, which are not suitable for large-scale multi-modal network analysis. In order to solve this problem, the present invention proposes a simple and comparable traffic impedance model based on the operational characteristics of five traffic modes. It integrates the characteristics of various transportation modes, considers the impedance of transportation modes such as roads, railways, aviation, and water transportation, and effectively supports the needs of integrated analysis of comprehensive transportation systems.

[0102] 2. Calibrate these impedance models based on real traffic data of various traffic modes. This will provide a solid theoretical basis for subsequent comprehensive traffic allocation, thereby effectively supporting traffic management and planning decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 It is a flow chart of calculating comprehensive transport impedance proposed by the present invention. DETAILED DESCRIPTION

[0104] In order to make the purpose and technical solution of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0105] like Figure 1 As shown, a method for calculating comprehensive transport impedance modeling described in the present invention specifically includes the following steps:

[0106] Step 1: Road transport time impedance modeling.

[0107] (1.1) Collect traffic data on roads of different levels, and use drones to take aerial videos of typical highways, national roads, and provincial roads during peak / off-peak hours on weekdays to collect data;

[0108] (1.2) Extract relevant data on roads of different grades, identify and count the traffic of four types of vehicles, namely small vehicles, medium-sized vehicles, empty container trucks, and large vehicles, based on deep learning methods, and extract traffic data; use Tracker software to set the scale and reference system, select target vehicles for automatic tracking, and extract real-time speed; use YOLOv4+deepsort target tracking algorithm, configure the target tracking model, and extract travel time;

[0109] (1.3) Analyze the operating characteristics of roads of different levels. Based on the data extracted above, analyze the traffic data on typical highways, national highways, and provincial highways to understand the basic characteristics of the relevant data and ensure that the traffic conditions considered in the model construction process are relatively comprehensive;

[0110] (1.4) Perform polynomial fitting on traffic data, let The fitting function is y=b1x+b2x 2 +b3x 3 +b4, use relevant software to write a program, calibrate the above three models according to the highway grade, and obtain the relevant calibration parameters.

[0111] Step 2: Railway transportation time impedance modeling.

[0112] (2.1) Obtain data related to conventional and high-speed railways, and extract data such as departure time, arrival time, departure station, arrival station, train type, train number, and ticket price;

[0113] (2.2) Construct railway impedance function model:

[0114] T=αL+βN+c

[0115] Where: T is the section travel time; L is the section length; N is the number of stops in the section; α, β, c are parameters to be determined;

[0116] (2.3) The impedance function model is calibrated using the relevant data of conventional railways and high-speed railways, respectively, to obtain the high-speed railway time impedance model and the conventional railway time impedance model.

[0117] Step 3: Water transport time impedance modeling.

[0118] (3.1) Obtain ship historical trajectory data and channel technical standard data, including ship type, position, speed, time, channel width and other information;

[0119] (3.2) Perform data screening. For missing data of some ships, classify them according to ship types, calculate the mean of length, width and draft data of different types of ships, and use it to fill the data;

[0120] (3.3) Taking a waterway within a specific range as the research object, we screened out the data that passed through this waterway for research, grouped the AIS data by ship name, and counted the data of ships that passed through the research waterway, including the length, width, etc. At the same time, we counted the distance and time that each group, i.e. each ship, passed through the waterway;

[0121] (3.3.1) Due to the width of the channel itself, ships do not follow a predetermined route when traveling in the channel. The distances traveled by different ships through the channel vary. To address this problem, the distance traveled by the ship is determined by accumulating the distances between the previous and next track points. The speed of the ship passing through the section is calculated based on the distance and the passing time.

[0122] (3.3.2) Based on the statistical data distribution, filter out the data that does not meet the requirements for sailing speed, sailing time, and sailing distance.

[0123] (3.4) Construct and calibrate the water transport impedance model

[0124] (3.4.1) Order Constructing the BPR polynomial regression model

[0125]

[0126] Where n is the degree of the polynomial, q is the ship flow rate of the channel section, C is the actual capacity of the channel section, L is the length of the channel section, and v f is the speed at which the ship freely passes through the channel section, and α and β are the unknown parameters of the model.

[0127] (3.4.2) Parameter calibration based on known data

[0128] Step 4: Air transport time impedance modeling.

[0129] (4.1) Obtain flight dynamic data and airport static data, including aircraft real-time position, speed, take-off and landing time, delay reasons, airport final approach, number of runways, etc.;

[0130] (4.2) Preprocess the data and select flights between the airports under study. Extract route characteristics including route length, flight speed, route free flight time, etc., airport characteristics including airport load factor, number of airport runways, etc., and flight characteristics including average travel time, take-off / landing delay time, average travel price, etc.;

[0131] Departure flight delay time:

[0132]

[0133] Among them, T D Departure flight delay time, is the actual departure time of the flight, The total travel time cost for a traveler taking a flight scheduled for departure time is:

[0134] T=t+T D

[0135] Among them, T is the total travel time cost of the traveler taking the flight, and t is the actual flight time of the flight, which includes the flight landing queue time, that is, the time the flight spends circling over the landing airport waiting to land due to the limited take-off and landing capacity of the airport runway.

[0136] (4.3) The following aviation impedance function model based on the landing airport runway load factor is constructed and calibrated:

[0137]

[0138] Where t is the flight travel time, that is, the time interval between the actual landing time and the actual take-off time of the flight; t0 is the flight free flow time; q d The flight flow at the landing airport; d Airport runway capacity for landing; is the landing airport runway load coefficient; α, β are model parameters.

[0139] (4.4) Construct the following flight travel time improvement model and calibrate it

[0140] The model is further improved by adding the departure airport traffic saturation variable and refitting the model. The improved model is expressed as:

[0141]

[0142] In the formula, q o is the flight flow of the departure airport; c o is the runway capacity of the take-off airport; α, β, m, n are model parameters. The meanings of other symbols are the same as above.

[0143] Step 5: Hub transit time impedance modeling.

[0144] (5.1) Obtain the minute-by-minute passenger flow into the hub, the length of time passengers depart in advance, and the travel time to the hub station.

[0145] (5.2) Based on the obtained data, a time impedance model for hub transfer is constructed and calibrated. A linear model is used to represent the relationship between the length of advance departure time and the inbound flow and travel time.

[0146] t A =a+bq+ct j

[0147] Among them, t A represents the length of time that passengers depart in advance; q represents the passenger flow when entering the station; t j represents the travel time of passengers arriving at the station; a, b, c are fitting parameters.

[0148] Step 6: Comprehensive Traffic Allocation

[0149] (6.1) According to the above steps, the impedance model of five modes of transportation, namely road, rail, water, aviation, and hub transfer, is obtained, and the impedance characteristics of each mode of transportation are analyzed.

[0150] (6.2) Considering the impedance model and characteristics of each transportation mode, comprehensive traffic allocation is carried out in combination with the route selection model.

[0151] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for comprehensive transportation impedance modeling, characterized by: This method establishes time impedance models according to the travel characteristics of highway traffic, railway traffic, waterway traffic, aviation traffic and hub transfer characteristics. The travel characteristics of highway traffic include traffic data on highways of different grades, as well as flow, speed, and travel time data. Polynomial fitting is performed on three grades of roads through flow, speed, and travel time data to construct polynomial time impedance models for highways of different grades. Railway transportation includes conventional railways and high-speed railways. The characteristics of railway transportation include departure time, arrival time, departure station, arrival station, train type, train number, and fare data. Time impedance models are constructed for conventional railways and high-speed railways respectively. The travel characteristics of waterway transportation are to extract AIS trajectory data from historical ship trajectory data as ship passage data; the sample unit is converted from ship trajectory points to ship navigation process, and a polynomial time impedance model for waterway transportation is constructed; The travel characteristics of air traffic include flight and airport data, which are extracted and analyzed to construct an air transport time impedance model; Hub transfer characteristics include hub inbound traffic and passenger arrival travel time data, and the data is extracted and analyzed to build a time impedance model for hub transfer; Comprehensive traffic allocation is performed based on the highway polynomial time impedance model, conventional railway and high-speed railway construction time impedance model, water transport polynomial time impedance model, air transport time impedance model, hub transfer time impedance model and route selection model.

2. The method of comprehensive transportation impedance modeling according to claim 1, characterized in that: In the travel characteristics of highway traffic, different levels of highways are divided into: expressways, provincial roads, and national roads; the steps for establishing the time impedance model are as follows: (1.1) Collect traffic data on roads of different levels, and use drones to take aerial videos of typical highways, national roads, and provincial roads during peak / off-peak hours on weekdays to collect data; (1.2) Extract relevant data on roads of different grades, identify and count the traffic of four types of vehicles: small vehicles, medium-sized vehicles, empty container trucks, and large vehicles based on deep learning methods, and extract traffic data; (1.3) Based on the data extracted in (1.2), analyze the operating characteristics of roads of different levels and obtain traffic data on typical highways, national highways, and provincial highways; (1.4) Perform polynomial fitting on traffic data on typical highways, national roads, and provincial roads: make: The fitting function is: y=b1x+b2x 2 +b3x 3 +b4 Among them, t is the vehicle travel time; t0 is the free flow travel time; q is the traffic flow; c is the design capacity; b1, b2, b3, b4 are the parameters to be fitted; The calibration parameters for expressways, national roads and provincial roads are as follows: Highway: y h =-0.604x+12.50(x) 2 +16.23(x) 3 +2.133; National Highway: -0.931x+4.719(x) 2 -3.513(x) 3 +1.411; Dart: -2.249x+8.627(x) 2 -6.922(x) 3 +1.

559.

3. The method of comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps for constructing the time impedance model of conventional railway and high-speed railway are as follows: (2.1) Obtain data related to conventional and high-speed railways, and extract data such as departure time, arrival time, departure station, arrival station, train type, train number, and ticket price; (2.2) Construct railway impedance function model: T=αL+βN+c Where: T is the section travel time; L is the length of the road section; N is the number of stops in the section; α, β, c are parameters to be determined; (2.3) Using the relevant data of conventional railways and high-speed railways, the impedance function model is calibrated to obtain the high-speed railway time impedance model and the conventional railway time impedance model; Get the calibration results of high-speed rail time and ordinary rail time: High-speed rail: T=0.0031*L+0.2098*N+0.1731 Ordinary Railway: T=0.0121*L+0.1980*N-0.0745.

4. The method of comprehensive transportation impedance modeling according to claim 1, characterized in that: The polynomial time impedance model of water transport is constructed as follows: (3.1) Obtain ship historical trajectory data and waterway technical standard data, including ship type, position, speed, time, and waterway width information; (3.2) Construct and calibrate the water transport impedance model; The BPR function is introduced into the water transport impedance modeling, and the maximum speed of all ships passing through the water transport section is selected as the free passing speed; the water transport impedance model is: Where L is the length of the water transport section. In the water transport impedance study, q is the ship flow of the waterway section, C is the actual traffic capacity of the waterway section, L is the length of the waterway section, and v f The speed at which the ship freely passes through the channel section, the two parameters α and β need to be calibrated in combination with the data; The model is transformed as follows: y = βx + lnα; The BPR polynomial regression model is constructed based on the above formula as follows: Where n is the degree of the polynomial; (3.4.4) According to the known data, the parameters are calibrated and the necessary parameters of water transport impedance are obtained as follows: (3.4.5) The water transport BPR model is transformed into a polynomial and the independent variables are upgraded to polynomial linear fitting. The fitting results are as follows.

5. The method for comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps to construct the air transportation time impedance model are as follows: (4.1) Obtain flight dynamic data and airport static data, including aircraft real-time position, speed, take-off and landing time, delay reasons, airport final approach, and runway number data; (4.2) Departure flight delay time is: Among them, T D Departure flight delay time, is the actual departure time of the flight, To plan the departure time; The total travel time cost for a traveler taking a flight is: T=t+T D Among them, T is the total travel time cost of the traveler taking the flight, and t is the actual flight time of the flight; (4.3) The following aviation impedance function model based on the landing airport runway load coefficient is constructed as follows: Where t is the actual flight time of the flight, that is, the time interval between the actual landing time and the actual take-off time of the flight; t0 is the free flow time of the flight; q d The flight flow at the landing airport; d Airport runway capacity for landing; is the landing airport runway load factor; α, β are model parameters; Calibrate according to the parameters, the result is: (4.4) Construct the flight travel time to update the aviation impedance function model and calibrate it: The take-off airport traffic saturation variable is further added to the model to improve the above model and refit the model; the updated aviation impedance function model expression is: In the formula, q o is the flight flow of the departure airport; c o is the runway capacity of the take-off airport; α, β, m, n are model parameters; The updated calibration results of the aviation impedance function model are:

6. The method of comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps to construct the time impedance model of hub transfer are as follows: (5.1) Obtain the minute-by-minute passenger flow in the hub, the length of time passengers depart in advance, and the travel time to the hub station; (5.2) Based on the data obtained in (5.1), a linear model is used to express the relationship between the advance departure time and the inbound flow and travel time to construct a time impedance model for hub transfer, which is expressed as follows: t A =a+bq+ct j Among them, t A represents the length of time that passengers depart in advance; q represents the passenger flow when entering the station; t j represents the travel time of passengers arriving at the station; a, b, c are fitting parameters. The calibration results are: t A =48.68+0.036q+0.795t j 。 7. The method of comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps of step 6 are as follows: (6.1) According to the above steps, the impedance model of five modes of transportation, namely road, rail, water, aviation, and hub transfer, is obtained, and the impedance characteristics of each mode of transportation are analyzed; (6.2) Considering the impedance model and characteristics of each transportation mode, the route selection model is combined to carry out comprehensive traffic allocation. The integrated traffic allocation of the comprehensive transportation network adopts the improved Logit path selection model and node allocation algorithm. (6.2.1) For the traffic volume w between the starting point O and the end point D ij First, we analyze the effective travel path from the starting point O to the end point D on the comprehensive transportation network. (6.2.2) Using the traffic impedance function proposed above to analyze the comprehensive traffic impedance of each effective travel path, the improved Logit path selection model is proposed as follows: Where P(I,J,y) is w ij The allocation rate on the yth travel path, F y 、F U are the comprehensive traffic impedances of the yth and Uth travel routes respectively; is the average authority comprehensive traffic impedance of each travel path under all transportation modes; η is the traffic allocation parameter of the comprehensive transportation network; v is the number of effective travel routes in the comprehensive transportation network; Where P(I,J,y) is w ij The allocation rate on the yth travel path, F y 、F U are the comprehensive transportation impedances of the yth and Uth travel routes, including the sum of the impedances of all transportation modes on the route; The impedance of each mode of transportation is calculated by the time impedance model and calibration results of road transportation, railway transportation, water transportation, air transportation, and hub transfer; The average comprehensive transportation impedance of each travel route under all transportation modes is calculated by the time impedance model and calibration results of road transportation, railway transportation, water transportation, air transportation, and hub transfer. η is the traffic allocation parameter of the comprehensive transportation network; v is the number of effective travel routes in the comprehensive transportation network.

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