A method for modeling comprehensive transportation impedance

Abstract

The application relates to a method for establishing a comprehensive traffic impedance model, belonging to the technical fields of transportation engineering and intelligent traffic technology. According to the trip characteristics of highway traffic, the trip characteristics of railway traffic, the trip characteristics of waterway traffic, the trip characteristics of aviation traffic and the hub transfer characteristics, a time impedance model is respectively established; according to the highway polynomial time impedance model, the time impedance model constructed by general railway and high-speed railway, the waterway transportation polynomial time impedance model, the aviation transportation time impedance model and the hub transfer time impedance model, the comprehensive traffic distribution is carried out in combination with a route selection model. According to the operation characteristics of five traffic modes, a simple and comparable traffic impedance model is provided. The characteristics of various traffic modes are comprehensively considered, the impedance of highway, railway, aviation, waterway and other transportation modes is considered, and the demand of integrated analysis of the comprehensive traffic system is effectively supported.

Description

Technical Field

[0001] This invention relates to a method for establishing a comprehensive transportation impedance model, belonging to the fields of transportation engineering and intelligent transportation technology. Background Technology

[0002] Integrated transportation impedance analysis is a crucial step in achieving integrated analysis of comprehensive transportation systems. The accuracy of impedance analysis for each mode has a significant, even decisive, impact on processes such as transportation time and cost calculation, traffic demand distribution analysis, traffic route selection and prediction, and integrated traffic flow allocation. Existing traffic impedance research primarily focuses on highway transportation, with relatively mature research techniques and a series of classic models, including the US Federal Highway Administration model. However, there is limited research on impedance analysis for other modes of transportation such as rail, air, water, and pipeline, which cannot effectively support the needs of integrated analysis of comprehensive transportation systems. This is specifically manifested in the following aspects:

[0003] ① The lack of analysis on the capacity of bottleneck sections and the delays at key points in transportation modes such as railways, aviation, and waterways makes it impossible to accurately predict the evolution of transportation time for each mode;

[0004] ② The lack of analysis on impedance factors such as convenience, comfort, and safety of various modes of transportation makes it impossible to fully reflect the differences in travelers' mode of transportation choices;

[0005] ③ There is a lack of research on the impedance of integrated transportation hubs, making it impossible to effectively analyze the impact of mode switching on passenger and freight transportation. Summary of the Invention

[0006] Purpose of the invention: To address the above-mentioned shortcomings, this invention discloses a method for calculating the impedance model of integrated transportation, breaking through the technical bottlenecks in impedance analysis and modeling of various modes, and systematically solving the problems that are common in current impedance research, such as unclear transportation characteristics of various modes, inconsistent model parameter calibration, and poor applicability.

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

[0008] A method for comprehensive transportation impedance modeling is proposed, which establishes time impedance models based on the travel characteristics of road traffic, rail traffic, waterway traffic, air traffic, and hub transfer characteristics respectively.

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

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

[0011] The travel characteristics of waterway transportation are as follows: AIS trajectory data is extracted from historical ship trajectory data to form ship passage data; the sample unit is transformed from ship trajectory points to ship navigation process, and a polynomial time impedance model of waterway transportation is constructed.

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

[0013] The characteristics of hub transfer include hub inbound traffic and passenger arrival travel time data. The data is extracted and analyzed to construct a time impedance model for hub transfer.

[0014] Based on the aforementioned polynomial time impedance models for highways, conventional railways and high-speed railways, waterway transportation, air transportation, and hub transfer, combined with the route selection model, comprehensive traffic allocation is carried out.

[0015] The method for comprehensive transportation impedance modeling described in this invention classifies highways into different grades: expressways, provincial highways, and national highways, based on their travel characteristics. The steps for establishing the time impedance model are as follows:

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

[0017] (1.2) Extract relevant data on highways of different grades, identify and count the traffic flow of four types of vehicles, namely small cars, medium-sized cars, empty container trucks and large cars, based on deep learning methods, and extract traffic flow 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 to configure target tracking model and extract travel time.

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

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

[0020] make:

[0021]

[0022] The fitting function is:

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

[0024] Where 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] Using relevant software, a program was written to calibrate the above three models (expressway, national highway, and provincial highway) according to their highway classifications, and the relevant calibration parameters were obtained. The results are as follows:

[0026] The calibration parameters for expressways, national highways, and provincial highways are described below:

[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] Provincial Highway: -2.249x + 8.627(x) 2 -6.922(x) 3 +1.559.

[0030] The method for comprehensive transportation impedance modeling described in this invention includes the following steps for constructing time impedance models for conventional and high-speed railways:

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

[0032] (2.2) Constructing the railway impedance function model:

[0033] T=αL+βN+c

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

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

[0036] The calibration results for high-speed rail time and conventional rail time were obtained:

[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 integrated transportation impedance modeling method described in this invention constructs a polynomial time impedance model for waterway transportation as follows:

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

[0043] (3.2) Perform data filtering. For cases where some ship data is missing, calculate the average values ​​of ship length, beam and draft data for different ship categories according to ship category, and use them to fill in the missing data.

[0044] (3.3) Taking a specific range of waterways as the research object, select data that pass through the selected waterways for study, and statistically analyze the passage data of the studied waterways, that is, the distance and time of each vessel passing through the waterways. The distance traveled by the vessel is determined by accumulating the distances of the preceding and following trajectory points, and the speed of the passage segment is calculated based on the distance and passage time.

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

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

[0047]

[0048] Where L is the length of the waterway segment. In the study of waterway impedance, q is the vessel flow rate of the channel segment, C is the actual throughput capacity of the channel segment, L is the length of the channel segment, and v... f For the speed at which ships freely pass through the channel section, considering the differences between water transport and road transport in actual conditions, the two parameters α and β need to be calibrated in conjunction with data;

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

[0050]

[0051]

[0052] y = βx + lnα;

[0053] (3.4.3) To obtain a better fit, the BPR multinomial 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) Based on the known data, the parameters for waterway transportation impedance calibration are obtained as follows:

[0057]

[0058] (3.4.5) The water transport BPR model is transformed into a polynomial model, 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 described in this invention includes the following steps for constructing an air transport time impedance model:

[0061] (4.1) Obtain flight dynamic data and airport static data, including real-time aircraft position, speed, take-off and landing time, reasons for delays, airport five-sided approach, and number of runways;

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

[0063] Airport characteristics include data such as airport load factor and number of runways, while flight characteristics include data such as average travel time and takeoff / landing delay time; among which

[0064] The flight departure delay time is:

[0065]

[0066] Among them, T D For flight departure delays, This refers to the actual departure time of the flight. For the planned departure time;

[0067] The total travel time cost for travelers taking flights is:

[0068] T = t + T D

[0069] Where T is the total travel time cost for travelers taking flights, and t is the actual flight time.

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

[0071]

[0072] In the formula, t represents the actual flight time, i.e., the time interval between the actual landing time and the actual takeoff time; t0 represents the free-flow time of the flight; q d For airport flight traffic; c d For the capacity of the airport runway for landing; α represents the runway load factor for the landing airport; β represents the model parameters.

[0073] The calibration was performed based on the parameters, and the results are as follows:

[0074]

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

[0076] The model was further improved by incorporating the takeoff airport traffic saturation variable, and then refitted. The updated aviation impedance function model expression is as follows:

[0077]

[0078] In the formula, q o For the departure airport's flight traffic; c o α represents the runway capacity of the takeoff airport; α, β, m, and n are model parameters.

[0079] The updated calibration results of the aeronautical impedance function model are as follows:

[0080]

[0081] The method for comprehensive transportation impedance modeling described in this invention constructs a time impedance model for hub transfers, and the steps are as follows:

[0082] (5.1) Obtain the passenger flow entering the hub every minute, the passenger departure time and the travel time to the hub station;

[0083] (5.2) Based on the data obtained in (5.1), a time impedance model for hub transfer is constructed using a linear model to represent the relationship between advance departure time, inbound traffic, and travel time. The expression is as follows:

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

[0085] Among them, t A q represents the time passengers departed in advance; t represents the passenger flow rate when entering the station; j The time taken for passengers to arrive at their destination is represented by ; a, b, and c are the fitting parameters.

[0086] The calibration results are as follows:

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

[0088] The method for comprehensive transportation impedance modeling described in this invention includes the following steps in step 6:

[0089] (6.1) Based on the above steps, the impedance models of the five modes of transportation—road, rail, waterway, air, and hub transfer—are obtained, and the impedance characteristics of each mode of transportation are analyzed.

[0090] (6.2) Considering the impedance models and characteristics of each mode of transportation, integrated traffic assignment is performed in conjunction with the route selection model. The integrated traffic assignment of the comprehensive transportation network adopts an improved Logit path selection model and node allocation algorithm.

[0091] (6.2.1) For the traffic volume w between the traffic origin O and the traffic destination D ij First, we analyze the effective travel routes from origin O to destination D on the integrated transportation network.

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

[0093]

[0094] In the formula, P(I,J,y) represents w ij The allocation rate F on the y-th travel path y F U The total traffic impedance of the y-th and U-th travel routes are respectively; η represents the average authority-based integrated traffic impedance for each travel path under all transportation modes; η is the traffic assignment parameter of the integrated transportation network; and v is the number of effective travel routes in the integrated transportation network.

[0095] In the formula, P(I,J,y) represents w ij The allocation rate F on the y-th travel path y F U These are the total traffic impedances for the y-th and U-th travel routes, respectively, including the sum of the impedances of all modes of transport on the routes;

[0096] The impedance of each mode of transportation is calculated from the time impedance models and calibration results of road transportation, rail transportation, water transportation, air transportation, and hub transfer.

[0097] F represents the average overall traffic impedance of each travel route under all transportation modes, calculated from the time impedance models and calibration results of road traffic, rail traffic, waterway traffic, air traffic, and hub transfer.

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

[0099] Beneficial effects

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

[0101] 1. Existing research primarily focuses on traffic impedance of highways, with less attention paid to impedance models for other transportation modes. Most models are designed for traffic operation rather than planning, often resulting in incomparability or excessively high computational costs, making them unsuitable for large-scale multimodal network analysis. To address this issue, this invention proposes a simple and comparable traffic impedance model based on the operational characteristics of five transportation modes. It integrates the characteristics of various transportation modes, considering the impedance of highways, railways, aviation, and waterways, effectively supporting the needs of integrated analysis of comprehensive transportation systems.

[0102] 2. Based on real traffic data from various traffic modes, calibrate these impedance models. This will provide a solid theoretical foundation for subsequent integrated traffic allocation, thereby effectively supporting traffic management and planning decisions. Attached Figure Description

[0103] Figure 1 This is a flowchart of the calculation of integrated transportation impedance proposed in this invention. Detailed Implementation

[0104] To make the objectives and technical solutions of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0105] like Figure 1 As shown, the method for calculating integrated transport impedance modeling according to the present invention specifically includes the following steps:

[0106] Step 1: Modeling the time impedance of highway transportation.

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

[0108] (1.2) Extract relevant data on highways of different grades, identify and count the traffic flow of four types of vehicles, namely small cars, medium-sized cars, empty container trucks and large cars, based on deep learning methods, and extract traffic flow 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 to configure target tracking model and extract travel time.

[0109] (1.3) Analyze the operational characteristics of roads of different levels. Based on the data extracted above, analyze the traffic data on typical expressways, national highways and provincial highways to understand the basic characteristics of the relevant data and ensure that the traffic conditions can be considered more comprehensively during the model construction process.

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

[0111] Step 2: Modeling the time impedance of railway transportation.

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

[0113] (2.2) Constructing the railway impedance function model:

[0114] T=αL+βN+c

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

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

[0117] Step 3: Modeling the time impedance of waterway transportation.

[0118] (3.1) Obtain historical trajectory data of ships and waterway technical standard data, including information such as ship type, position, speed, time, and waterway width;

[0119] (3.2) Perform data filtering. For cases where some vessel data is missing, calculate the average values ​​of vessel length, beam, and draft data for different vessel categories according to vessel category, and use them to fill in the missing data.

[0120] (3.3) Taking a specific range of waterways as the research object, select the data that passes through this waterway for research, group the AIS data by ship name, and count the ship data that passes through the research waterway, including ship length, ship width, etc. At the same time, count the distance and time of each group, that is, each ship passing through the waterway.

[0121] (3.3.1) Due to the width of the waterway itself, ships do not travel in the waterway according to a predetermined route. The distance that different ships travel through the waterway varies. To address this issue, the distance traveled by ships is determined by accumulating the distances of the preceding and following trajectory points. The speed of the passage segment is calculated based on the distance and the passage time.

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

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

[0124] (3.4.1) Let Constructing a BPR multinomial regression model

[0125]

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

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

[0128] Step 4: Modeling the time impedance of air transport.

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

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

[0131] The flight departure delay time is:

[0132]

[0133] Among them, T D For flight departure delays, This refers to the actual departure time of the flight. The total travel time cost for travelers taking a flight at the planned departure time is:

[0134] T = t + T D

[0135] Where T represents the total travel time cost for travelers, and t represents the actual flight time, which includes the landing queue time, i.e. the time that flights spend circling and waiting to land at the airport due to the limited takeoff and landing capacity of the airport runway.

[0136] (4.3) Construct and calibrate the following aviation impedance function model based on the runway load factor of the landing airport:

[0137]

[0138] In the formula, t represents the flight travel time, i.e., the time interval between the actual landing time and the actual takeoff time; t0 represents the free-flow travel time; q d For airport flight traffic; c d For the capacity of the airport runway for landing; α represents the runway load factor for the landing airport; β and α are model parameters.

[0139] (4.4) Construct and calibrate the following improved flight travel time model.

[0140] The model was further improved by incorporating the departure airport traffic saturation variable, and then refitted. The improved model is expressed as follows:

[0141]

[0142] In the formula, q o For the departure airport's flight traffic; c o Let be the runway capacity of the takeoff airport; α, β, m, and n are model parameters. The meanings of the other symbols are the same as in the above formula.

[0143] Step 5: Modeling the time impedance of hub transfer.

[0144] (5.1) Obtain the passenger flow per minute within the hub, the passenger departure time, and the travel time to the hub station.

[0145] (5.2) Based on the obtained data, construct and calibrate a time impedance model for hub transfer. Use a linear model to represent the relationship between advance departure time, inbound traffic volume, and travel time.

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

[0147] Among them, t A q represents the time passengers departed in advance; t represents the passenger flow rate when entering the station; j The time taken for passengers to arrive at their destination is represented by ; a, b, and c are the fitting parameters.

[0148] Step Six: Integrated Traffic Allocation

[0149] (6.1) Based on the above steps, impedance models for five modes of transportation—road, rail, waterway, air, and hub transfer—are obtained, and the impedance characteristics of each mode of transportation are analyzed.

[0150] (6.2) Consider the impedance models and characteristics of each mode of transportation, and combine them with the route selection model to carry out comprehensive traffic allocation.

[0151] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for comprehensive transportation impedance modeling, characterized in that: This method establishes time impedance models based on the travel characteristics of road traffic, rail traffic, waterway traffic, air traffic, and hub transfer characteristics, respectively. Step 1: The travel characteristics of highway traffic include traffic data on highways of different grades, and data on flow rate, speed, and travel time; polynomial fitting is performed on the three grades of roads using the flow rate, speed, and travel time data to construct polynomial time impedance models for different grades of highways. Multinomial fitting was performed on traffic data from typical highways, national roads, and provincial roads: make: ； The fitting function is: ； in, For vehicle travel time; The travel time is during free flow. Traffic flow; To design traffic capacity; , , , These are the parameters to be fitted; Step 2: Railway transportation includes conventional trains and high-speed trains. Railway travel characteristics include departure time, arrival time, departure station, arrival station, train type, train number, and ticket price data; construct time impedance models for conventional trains and high-speed trains respectively. Constructing a railway impedance function model: ； In the formula: For segment travel time; The length of the road segment; This refers to the number of stops within the section. , , Undetermined parameters Step 3: The travel characteristics of waterway transportation are obtained by extracting AIS trajectory data from historical ship trajectory data to form ship passage data; the sample unit is transformed from ship trajectory points to ship navigation process, and a polynomial time impedance model for waterway transportation is constructed. Construct and calibrate the waterway transport impedance model; The BPR function is introduced into the waterway impedance model, and the maximum speed among all passing vessels on the waterway segment is selected as the free passage speed; the waterway transport impedance model is as follows: ； in, The length of the waterway section; in the study of waterway impedance For the vessel traffic flow in the waterway section, This refers to the actual traffic capacity of the waterway section. The length of the waterway section The speed at which ships can freely pass through the channel section, and The two parameters need to be calibrated using data; Step 4: The travel characteristics of air traffic include flight and airport data, and the flight and airport data are extracted and analyzed to construct an air transport time impedance model; The following aviation impedance function model is constructed based on the runway load factor of the landing airport: ； In the formula, The actual flight time is the time interval between the actual landing time and the actual takeoff time. Free-flow travel time for flights; For airport flight traffic; For the capacity of the airport runway for landing; This refers to the runway load factor at the landing airport. , These are model parameters; Construct a flight itinerary time update aviation impedance function model: The model was further improved by incorporating the takeoff airport traffic saturation variable, and then refitted. The updated aviation impedance function model expression is as follows: ； In the formula, Flight traffic at the departure airport; For the capacity of the airport runway for takeoff; , , , These are model parameters; Step 5: Hub transfer characteristics include hub inbound traffic and passenger arrival travel time data. The data is extracted and analyzed to construct a time impedance model for hub transfer. A time impedance model for hub transfer is constructed by using a linear model to represent the relationship between advance departure time, inbound traffic volume, and travel time. The expression is as follows: ； in, Indicates the amount of time the passenger has to depart in advance; This indicates the passenger flow when entering the station; Indicates the travel time for passengers to arrive at the station; These are the fitting parameters; Step 6: Based on the aforementioned polynomial time impedance model for highways, time impedance models for conventional and high-speed railways, polynomial time impedance models for waterway transportation, time impedance models for air transportation, and time impedance models for hub transfers, combined with the route selection model, perform comprehensive traffic allocation.

2. The method for 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 highways, and national highways; the steps for establishing the time impedance model are as follows: (1.1) Collect traffic data on highways of different grades, and use drones to take aerial videos of typical highways, national highways and provincial highways during weekday peak / off-peak travel times and collect data; (1.2) Extract relevant data from highways of different grades, identify and count the traffic flow of four types of vehicles—small cars, medium-sized cars, empty container trucks, and large cars—based on deep learning methods, and extract traffic flow data; (1.3) Based on the data extracted in (1.2), analyze the operational characteristics of roads of different levels to obtain traffic data on typical expressways, national highways, and provincial highways; (1.4) Perform polynomial fitting on traffic data from typical expressways, national highways, and provincial highways: make: ； The fitting function is: ； in, For vehicle travel time; The travel time is during free flow. Traffic flow; To design traffic capacity; , , , These are the parameters to be fitted; The calibration parameters for expressways, national highways, and provincial highways are described below: highway: ; National Highway: ; Provincial Highway: .

3. The method for comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps for constructing time impedance models for conventional and high-speed railways are as follows: (2.1) Obtain relevant data on conventional and high-speed trains, and extract data on departure time, arrival time, departure station, arrival station, train type, train number, and ticket price; (2.2) Constructing the railway impedance function model: ； In the formula: For segment travel time; The length of the road segment; This refers to the number of stops within the section. , , These are parameters to be determined. (2.3) Using relevant data from conventional railways and high-speed railways respectively, the impedance function model was calibrated to obtain the time impedance model of high-speed railways and the time impedance model of conventional railways; The calibration results for high-speed rail time and conventional rail time were obtained: High-speed rail: ； Ordinary railway: 。 4. The method for comprehensive transportation impedance modeling according to claim 1, characterized in that: The polynomial time impedance model for waterway transportation is constructed as follows: (3.1) Obtain historical trajectory data of ships and waterway technical standard data, including information on ship type, position, speed, time, and waterway width; (3.2) Construct and calibrate the waterway transport impedance model; The BPR function is introduced into the waterway impedance model, and the maximum speed among all passing vessels on the waterway segment is selected as the free passage speed; the waterway transport impedance model is as follows: ； in, The length of the waterway section; in the study of waterway impedance For the vessel traffic flow in the waterway section, This refers to the actual traffic capacity of the waterway section. The length of the waterway section The speed at which ships can freely pass through the channel section, and The two parameters need to be calibrated using data; (3.3) The model is transformed as follows, let: ； ； ； Based on the above formula, the BPR multinomial regression model is constructed as follows: ； in, Let the degree be the polynomial. (3.4.4) Based on the known data, the parameters are calibrated, and the necessary parameters of the waterway transport impedance are obtained as follows: ； (3.4.5) The water transport BPR model is transformed into a polynomial model, 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 an air transport time impedance model are as follows: (4.1) Obtain flight dynamic data and airport static data, including real-time aircraft position, speed, take-off and landing time, reasons for delays, airport five-sided approach, and runway number data; (4.2) The delay time for the departing flight is: ； in, For flight departure delays, This refers to the actual departure time of the flight. For the planned departure time; The total travel time cost for travelers taking flights is: ； in, The total travel time cost for travelers taking flights. This refers to the actual flight time. (4.3) The following aviation impedance function model based on the runway load factor of the landing airport is constructed as follows: ； In the formula, The actual flight time is the time interval between the actual landing time and the actual takeoff time. Free-flow travel time for flights; For airport flight traffic; For the capacity of the airport runway for landing; This refers to the runway load factor at the landing airport. , These are model parameters; The calibration was performed based on the parameters, and the results are as follows: ； (4.4) Construct and calibrate the flight itinerary time update aviation impedance function model: The model was further improved by incorporating the takeoff airport traffic saturation variable, and then refitted. The updated aviation impedance function model expression is as follows: ； In the formula, Flight traffic at the departure airport; For the capacity of the airport runway for takeoff; , , , These are model parameters; The updated calibration results of the aeronautical impedance function model are as follows: 。 6. The method for comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps to construct a time impedance model for hub-and-spoke transfer are as follows: (5.1) Obtain the passenger flow entering the hub every minute, the passenger departure time and the travel time to the hub station; (5.2) Based on the data obtained in (5.1), a time impedance model for hub transfer is constructed using a linear model to represent the relationship between advance departure time, inbound traffic, and travel time. The expression is as follows: ； in, Indicates the amount of time the passenger has to depart in advance; This indicates the passenger flow when entering the station; Indicates the travel time for passengers to arrive at the station; These are the fitting parameters; The calibration results are as follows: 。 7. The method for comprehensive transportation impedance modeling according to claim 1, characterized in that: The steps in step 6 are as follows: (6.1) Based on steps 1-5 above, the impedance models of the five modes of transportation—road, rail, waterway, air, and hub transfer—are obtained, and the impedance characteristics of each mode of transportation are analyzed. (6.2) Considering the impedance models and characteristics of each mode of transportation, and combining the route selection model, comprehensive traffic assignment is carried out; the integrated traffic assignment of the comprehensive transportation network adopts the improved Logit path selection model and node assignment algorithm. (6.2.1) Traffic volume between the origin O and the destination D First, we analyze the effective travel routes from origin O to destination D on the integrated transportation network. (6.2.2) Using the traffic impedance function proposed above to analyze the comprehensive traffic impedance of each effective travel path, an improved Logit path selection model is proposed as follows: ； In the formula, for In the Allocation rate on each travel route , The first Article, No. The overall traffic impedance of the entire travel route; The average authority-based integrated traffic impedance for each travel route across all transportation modes; Assign traffic parameters to the integrated transportation network; The number of effective travel routes in the integrated transportation network; In the formula, for In the Allocation rate on each travel route , The first Article, No. The overall traffic impedance of the entire travel route, including the sum of the impedances of all modes of transportation on the route; The impedance of each mode of transportation is calculated from the time impedance models and calibration results of road transportation, rail transportation, water transportation, air transportation, and hub transfer. The average overall traffic impedance for each travel route under all transportation modes is calculated from the time impedance models and calibration results of road traffic, rail traffic, waterway traffic, air traffic, and hub transfer. Assign traffic parameters to the integrated transportation network; This represents the number of effective travel routes within the integrated transportation network.

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