A method and system for port area collection and distribution freight channel toll station lane configuration considering capacity control

Abstract

This invention discloses a method and system for lane configuration at toll stations in port freight transport corridors, considering capacity control. The method includes the following steps: S1, acquiring traffic flow data of vehicles arriving upstream at the toll station entrance / exit, and downstream road capacity data; S2, determining whether to implement a dynamic lane configuration strategy; S3, establishing a lane configuration optimization model for the toll station with the optimization objective of minimizing the operating cost and total vehicle delay cost of the freight transport corridor toll station, and adding constraints; S4, iteratively solving the lane configuration optimization model to determine the lane configuration strategy. This invention improves the service level of toll stations in freight transport corridors, refines toll station queuing management and lane configuration methods, and provides a holistic layout scheme for dedicated lanes.

Description

Technical Field

[0001] This invention belongs to the field of highway toll station lane configuration, specifically relating to a method and system for configuring toll station lanes in port area freight transport channels that takes capacity control into account. Background Technology

[0002] In recent years, with the continuous improvement of my country's opening-up level and the rapid increase in import and export trade, the throughput of seaports has also risen accordingly. However, the construction of supporting facilities and service systems for cargo collection and distribution has lagged behind, making it difficult to meet the rapidly growing freight demand. The freight traffic volume, characterized by uneven time distribution, has created a prominent contradiction with the limited toll station lane resources and road capacity. The use of ETC has improved the efficiency of entering and exiting high-grade freight corridors to some extent, but it has also brought new problems such as the mixing of ETC and MTC traffic. Therefore, it is urgent to improve the toll station release capacity of freight collection and distribution corridors by rationally configuring toll station lanes, taking into account the capacity of the main line of the collection and distribution corridor.

[0003] Currently, research on toll station management is mostly based on ordinary expressways, lacking research on the emerging scenario of expressways serving as freight transport corridors. This makes it difficult to adapt to the tidal changes in freight traffic volume with port loading and unloading demands. Furthermore, the actual capacity of the main line of high-grade freight highways is constantly changing due to the influence of upstream and downstream traffic flow, and existing toll station lane configuration methods fail to take the main line capacity into account. Summary of the Invention

[0004] To address the shortcomings of existing technologies, such as low service levels at toll stations along freight transport corridors, imperfect methods for queuing management and lane configuration, and limitations of dynamic lane configuration applications to ordinary highways, this paper proposes a lane configuration method and system for toll stations along freight transport corridors in port areas that considers capacity control, thereby better enabling lane configuration at highway toll stations along freight transport corridors.

[0005] To solve the above technical problems, the present invention provides the following technical solution: a method for configuring toll lanes at port freight transport channels considering capacity control, comprising the following steps:

[0006] S1. Obtain traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances;

[0007] S2. Based on traffic flow data and downstream road capacity data, determine whether to set a dynamic lane configuration strategy. If yes, proceed to step S3; otherwise, do not set a dynamic lane configuration strategy.

[0008] S3. Based on the traffic flow data and road capacity data of toll stations, with the optimization objective of minimizing the operating cost and total vehicle delay cost of toll stations on freight transport corridors, an optimization model for toll station lane configuration is established for toll stations on freight transport highways, and constraints are added.

[0009] S4. Based on real-time traffic flow data, road capacity data, and lane distribution of various types and directions, iteratively solve the toll station lane configuration optimization model to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

[0010] Furthermore, in step S1 above, the traffic flow of vehicles coming from upstream of the entrance toll station and upstream of the exit toll station by vehicle type is converted into traffic flow data according to a preset conversion factor; based on the number of lanes, the capacity of the highway toll station downstream of the entrance mainline is calculated according to the maximum hourly traffic volume.

[0011] Furthermore, the aforementioned step S2 includes the following sub-steps:

[0012] S201. Establish a database: containing traffic flow data and basic road parameters for the freight transport corridor connecting the toll station to the port.

[0013] S202. Calculate the non-uniformity coefficient D for manual toll lane entry, manual toll lane exit, ETC lane entry, and ETC lane exit. Min D Mout D Ein D Eout As shown in the following formula:

[0014]

[0015]

[0016]

[0017]

[0018] In the formula, σ is the standard deviation of the hourly traffic flow intensity as a percentage of the total traffic flow; λ Min λ represents the intensity of vehicles entering the collection and distribution channel from the manual toll lane. Mout λ represents the intensity of vehicles entering the collection and distribution channel from the manual toll lane. Ein To determine the intensity of vehicles entering the ETC (Electronic Toll Collection) and distribution channels, λ Eout The intensity of oncoming vehicles entering the ETC access lane;

[0019] S203, Set configuration parameter D:

[0020] D = max{D Min DMout , D Ein , D Eout}

[0021] If n < D < m, no dynamic lane configuration strategy is set; otherwise, a dynamic lane configuration strategy is set and step S3 is executed. n is the lower threshold value and m is the upper threshold value.

[0022] Furthermore, in the aforementioned step S3, the operating cost of the toll station on the freight collection and distribution channel is calculated as follows:

[0023] C op = a M (N Min + N Mout ) + a E (N Ein + N Eout )

[0024] In the formula, a M is the cost per yuan for opening 1 MTC, a E is the cost per yuan for opening 1 ETC, N Min is the number of lanes of vehicles entering the freight collection and distribution channel from the manual toll lane; N Min is the number of lanes of vehicles entering the freight collection and distribution channel from the manual toll lane, N Mout is the number of lanes of vehicles leaving the freight collection and distribution channel from the manual toll lane, N Ein is the number of lanes of vehicles entering the freight collection and distribution channel from the ETC lane, N Eout is the number of lanes of vehicles leaving the freight collection and distribution channel from the ETC lane;

[0025] The total vehicle delay cost corresponding to the toll station on the freight collection and distribution channel is calculated as follows:

[0026] C de = a D (λ Min W<00000...​​​​​​​​​​​​​​​​​​​​​​​​​​D To avoid wasting time and money.

[0028] Furthermore, in step S3 above, the constraints include:

[0029] (1) Capacity constraint: the traffic flow entering the toll station shall not exceed the capacity of the main line.

[0030]

[0031] r(k) is the calculated regulation rate, and the formula for calculating r(k) is as follows:

[0032] r(k) = c a -q d (k-1)

[0033] c a q represents the actual downstream capacity of the ramp (pcu / h). d (k-1) represents the upstream traffic demand of the ramp in the previous time period;

[0034] (2) Positive integer constraint: the number of all lanes must be a positive integer.

[0035] N Min N Ein N Mout N Eout ∈N*

[0036] (3) Total number of lanes constraint: The total number of all lanes shall not exceed the number of two-way lanes allowed by the road alignment.

[0037] N Min +N Ein +N Mout +N Eout =N T

[0038] (4) Ensure the capacity of off-ramp lanes; the combined capacity of ETC and MTC lanes exceeds the oncoming traffic intensity to avoid mainline congestion:

[0039]

[0040]

[0041] In the formula, E Mout E represents the average service time for vehicles leaving the collection and distribution channel from the manual toll lane. Ein E represents the average service time for vehicles entering the collection and distribution channel from the ETC lane. Eout Average service time for vehicles leaving the collection and distribution channel via ETC lane.

[0042] Furthermore, the toll station lane configuration optimization model in step S3 above is as follows:

[0043] min C op +C de

[0044]

[0045] N Min N Ein N Mout N Eout ∈N*

[0046] N E +N M +N ED +N MD ≤N T

[0047]

[0048]

[0049] Furthermore, the aforementioned W Min W Ein W Mout W Eout Calculate the following formulas respectively:

[0050]

[0051]

[0052]

[0053]

[0054] Among them, D Min D represents the service time variance of vehicles entering the distribution channel from the manual toll lane. Min D represents the service time variance of vehicles entering the distribution channel from the manual toll lane. Mout D represents the service time variance for vehicles leaving the collection and distribution channel from the manual toll lane. Ein D represents the service time variance for vehicles entering the collection and distribution channel from the ETC lane. Eout Variance of service time for vehicles leaving the ETC lane from the distribution channel. Min The average service time for vehicles entering the collection and distribution channel from the manual toll lane.

[0055] Another aspect of the present invention proposes a port freight channel toll station lane configuration system considering capacity control, comprising:

[0056] The data acquisition module is used to acquire traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances.

[0057] The strategy judgment module is used to determine whether to set a dynamic lane configuration strategy based on traffic flow data and downstream road capacity data. If so, it will enter the toll station lane configuration optimization model construction module to execute; otherwise, it will not set a dynamic lane configuration strategy.

[0058] The toll station lane configuration optimization model building module is used to establish a toll station lane configuration optimization model based on the toll station's traffic flow data and road capacity data, with the optimization objective of minimizing the operating cost and total vehicle delay cost of the freight transport corridor toll station. It also adds constraints to the toll station lane configuration optimization model for the freight transport highway.

[0059] The toll station lane configuration strategy solution module is used to iteratively solve the toll station lane configuration optimization model based on real-time traffic flow data, road capacity data, and the distribution of lanes of various types and directions, to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

[0060] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0061] 1. This invention takes the collection and distribution of freight transport channels as the research object. Through the characteristic analysis of collection and distribution of freight transport highways, considering the capacity distribution, it determines whether to set up a dynamic toll station lane number control strategy, and gives a specific configuration scheme for toll station lanes.

[0062] 2. This invention establishes an optimization model for toll stations on freight transport corridors based on traffic delay analysis, and provides a lane configuration method for toll stations on freight transport corridors from a theoretical perspective, thereby improving the solution speed while ensuring the scientific validity of this invention.

[0063] 3. This invention optimizes both lane direction and function, making it more suitable for the tidal nature of port traffic and the widespread adoption of ETC.

[0064] 4. This invention takes into account multiple parameters such as the main road capacity, the intensity of vehicles coming from upstream and downstream, and the traffic flow of different vehicle types, and provides a layout scheme for directional dedicated lanes from an overall perspective, which is more systematic and comprehensive;

[0065] 5. The directional dedicated lane delay optimization model established by this invention is not only applicable to freight collection and distribution channels, but also allows for flexible modification of model parameters based on the characteristics of the scenario, making this invention highly flexible and scalable. Attached Figure Description

[0066] Figure 1This is a flowchart of the method of the present invention.

[0067] Figure 2 The diagram shows a schematic representation of the lane configuration at a toll station according to an embodiment of the present invention. Detailed Implementation

[0068] To better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

[0069] In this invention, various aspects of the invention are described with reference to the accompanying drawings, in which numerous illustrative embodiments are shown. Embodiments of the invention are not limited to those depicted in the drawings. It should be understood that the invention is implemented through any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. Furthermore, some aspects of the invention disclosed may be used alone or in any suitable combination with other aspects of the invention disclosed.

[0070] refer to Figure 1 This invention provides a method for configuring lanes at toll stations in port freight transport corridors that takes capacity control into account, comprising the following steps:

[0071] S1. Obtain traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances;

[0072] S2. Based on traffic flow data and downstream road capacity data, determine whether to set a dynamic lane configuration strategy. If yes, proceed to step S3; otherwise, do not set a dynamic lane configuration strategy.

[0073] S3. Based on the traffic flow data and road capacity data of toll stations, with the optimization objective of minimizing the operating cost and total vehicle delay cost of toll stations on freight transport corridors, an optimization model for toll station lane configuration is established for toll stations on freight transport highways, and constraints are added.

[0074] S4. Based on real-time traffic flow data, road capacity data, and lane distribution of various types and directions, iteratively solve the toll station lane configuration optimization model to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

[0075] Preferably, in step S1, the traffic flow data of vehicles arriving upstream of the entrance toll station and upstream of the exit toll station, categorized by vehicle type, is converted into traffic flow data according to a preset conversion factor. Based on the number of lanes, the capacity of the highway toll station downstream of the mainline at the entrance is calculated using the maximum hourly traffic volume as the benchmark.

[0076] In accordance with the "Technical Standards for Highway Engineering (JTG B01-2014)", this invention converts traffic volume by vehicle type into equivalent traffic volume pcu / h using the following conversion factors, as shown in Table 1 below:

[0077] Table 1

[0078] Model Passenger car Mid-size car large vehicles Automobile train Conversion factor 1.0 1.5 2.5 4.0

[0079] Based on the number of lanes, the downstream road capacity (pcu / h) of the toll station entrance is calculated using the maximum hourly traffic volume under Level 5 service as the baseline capacity, as shown in Table 2 below:

[0080] Table 2

[0081] Design speed (km / h) 120 100 80 Passage capacity (pcu / (ln*h)) 2200 2100 2000

[0082] Preferably, step S2 includes the following sub-steps:

[0083] S201. Establish a database: The database contains traffic flow data and basic road parameters of the freight transport corridor connecting the toll station to the port. In the example, the toll station's entrance lanes and exit lanes include at least two toll types: MTC and ETC. The total number of toll station entrance and exit lanes is at least 6.

[0084] S202. Calculate the non-uniformity coefficient D for manual toll lane entry, manual toll lane exit, ETC lane entry, and ETC lane exit. Min D Mout D Ein D Eout As shown in the following formula:

[0085]

[0086]

[0087]

[0088]

[0089] In the formula, σ is the standard deviation of the hourly traffic flow intensity as a percentage of the total traffic flow; λ Min λ represents the intensity of vehicles entering the collection and distribution channel from the manual toll lane. Mout λ represents the intensity of vehicles entering the collection and distribution channel from the manual toll lane. Ein To determine the intensity of vehicles entering the ETC (Electronic Toll Collection) and distribution channels, λ Eout The intensity of oncoming vehicles entering the ETC access lane;

[0090] S203, Set configuration parameter D:

[0091] D = max{D Min DMout D Ein D Eout},

[0092] If n < D < m, then no dynamic lane configuration strategy is set; otherwise, a dynamic lane configuration strategy is set, and step S3 is executed. n is the lower limit threshold, m is the upper limit threshold, and in this example, it is 0.85 < D < 1.15.

[0093] Preferably, in step S3, the operating cost of the toll station for the freight transport corridor is calculated as follows:

[0094] C op =a M (N Min +N Mout )+a E (N Ein +N Eout )

[0095] In the formula, a M To open 1 MTC line, the cost is RMB, a E The cost of opening one ETC line is RMB / N Min N represents the number of lanes for vehicles entering the distribution and collection channel from the manual toll lane. Min N represents the number of lanes for vehicles entering the distribution and collection channel from the manual toll lane. Mout N represents the number of manual toll lanes that exit the access road. Ein N represents the number of lanes from the ETC lane to the access road. Eout This refers to the number of ETC lanes that exit the access road lanes;

[0096] The total vehicle delay cost corresponding to the toll stations on the freight transport corridor is calculated as follows:

[0097] C de =a D (λ Min W Min +λ Ein W Ein +λ Mout W Mout +λ Eout W Eout )

[0098] In the formula, W Min W represents the average queuing delay for vehicles entering the distribution channel from the manual toll lane. Min W represents the average queuing delay for vehicles entering the distribution channel from the manual toll lane. Mout W represents the average queuing delay for vehicles leaving the collection and distribution lane from the manual toll lane. Ein W represents the average queuing delay for vehicles entering the collection and distribution channel from the ETC lane. Eouta is the average queuing delay for vehicles leaving the ETC lane from the distribution channel. D To avoid wasting time and money.

[0099] The aforementioned W Min W Ein W Mout W Eout Calculate the following formulas respectively:

[0100]

[0101]

[0102]

[0103]

[0104] Among them, D Min D represents the service time variance of vehicles entering the distribution channel from the manual toll lane. Min D represents the service time variance of vehicles entering the distribution channel from the manual toll lane. Mout D represents the service time variance for vehicles leaving the collection and distribution channel from the manual toll lane. Ein D represents the service time variance for vehicles entering the collection and distribution channel from the ETC lane. Eout Variance of service time for vehicles leaving the ETC lane from the distribution channel. Min The average service time for vehicles entering the collection and distribution channel from the manual toll lane.

[0105] Preferably, the constraints in step S3 include:

[0106] (1) Capacity constraint: the traffic flow entering the toll station shall not exceed the capacity of the main line.

[0107]

[0108] r(k) is the calculated regulation rate, and the formula for calculating r(k) is as follows:

[0109] r(k) = c a -q d (k-1)

[0110] c a q represents the actual downstream capacity of the ramp (pcu / h). d (k-1) represents the upstream traffic demand of the ramp in the previous time period;

[0111] (2) Positive integer constraint: the number of all lanes must be a positive integer.

[0112] N Min N Ein N MoutN Eout ∈N*

[0113] (3) Total number of lanes constraint: The total number of all lanes shall not exceed the number of two-way lanes allowed by the road alignment.

[0114] N Min +N Ein +N Mout +N Eout =N T

[0115] (4) Ensure the capacity of off-ramp lanes; the combined capacity of ETC and MTC lanes exceeds the oncoming traffic intensity to avoid mainline congestion:

[0116]

[0117]

[0118] In the formula, E Mout E represents the average service time for vehicles leaving the collection and distribution channel from the manual toll lane. Ein E represents the average service time for vehicles entering the collection and distribution channel from the ETC lane. Eout Average service time for vehicles leaving the collection and distribution channel via ETC lane.

[0119] Furthermore, the optimization model for toll station lane configuration in step S3 is as follows:

[0120] min C op +C de

[0121]

[0122] N Min N Ein N Mout N Eout ∈N*

[0123] N E +N M +N ED +N MD ≤N T

[0124]

[0125]

[0126] The model is solved, and the results are sent to the toll station for execution. Dynamic lane indication boards are added 100m and 50m in front of the toll station to help drivers change lanes in time.

[0127] Taking the Tianjin Port cargo handling channel project as an example, such as Figure 2 As shown, this freight transport corridor has 6 ramps, corresponding to 6 peripheral roads intersecting with the corridor, from east to west: Haitie Avenue, Xinbei Road, Gangcheng Avenue, Ring Expressway, Changshen Expressway, and Jingjintang Expressway. The choice of Gangcheng Avenue as the entry point to the toll station is used as the basis.

[0128] Step S1: Obtain traffic flow from upstream of the entrance and exit toll stations of the Tianjin Port freight transport corridor, and downstream traffic capacity of the expressway mainline at the toll stations. Specific data and corresponding conversion steps include:

[0129] 1) Obtain the vehicle type-specific traffic flow values ​​veh / h for vehicles coming from upstream of the entrance toll station and the exit toll station of Gangcheng Avenue. Refer to the "Highway Engineering Technical Standard (JTG B01-2014)" and convert the vehicle type-specific traffic volume into equivalent traffic volume pcu / h according to the following conversion factor.

[0130] Since the access and distribution channels are not yet completed, traffic volume for a specific time period within a day is generated as a sample. The transformation process is illustrated using the total inbound traffic volume for one hour of the day as an example.

[0131]

[0132]

[0133] 2) The Tianjin Port cargo handling channels are constructed to highway and expressway standards with eight to twelve lanes in both directions. The main line is designed for a speed of 80 km / h. Therefore, the traffic capacity calculated based on a standard of ten lanes in both directions is 2000*5=10000pcu / (ln*h) in one direction.

[0134] Step S2: Determine whether the Tianjin Port freight transport corridor meets the basic requirements for setting up a dedicated lane. Since the freight transport corridor project is under construction, we need to use the virtual traffic generated in the previous step.

[0135] 1) Assume that the entrance and exit lanes of Gangcheng Avenue toll station include both MTC and ETC toll collection methods, and the total number of entrance and exit lanes of the toll station is 8.

[0136] 2) Determine if the flow rate is uniformly distributed:

[0137] The non-average coefficients for the four scenarios—entering through a manual toll lane, exiting through a manual toll lane, entering through an ETC lane, and exiting through an ETC lane—are D respectively. Min D Mout D Ein D Eout :

[0138]

[0139]

[0140]

[0141]

[0142] The traffic distribution over a week is shown in the table below.

[0143] time <![CDATA[λ Min ]]> <![CDATA[λ Mout ]]> <![CDATA[λ Ein ]]> <![CDATA[λ Eout ]]> Day 1 0:00-1:00 35 21 10 65 Day 1 1:00-2:00 22 14 27 19 …… …… …… …… …… Day 3 8:00-9:00 21 54 78 96 …… …… …… …… …… Day 7 23:00-24:00

[0144] D can be calculated Min =0.31, D Mout =0.26, D Mout =0.35, D Mout =0.24, a dynamic lane configuration strategy needs to be set.

[0145] Step S3: Use the grid search method to solve the lane configuration model of the port freight channel toll station considering capacity control, and obtain the minimum value of the objective function and the corresponding number of lanes N. Min N Ein N Mout N Eout .

[0146] Assume the traffic volume arriving in the previous time period is , and let a be the traffic volume arriving in the previous time period. D =0.2, the service time variances for entering and exiting manual toll lanes are D respectively. Mout =3,D Min =1, mean service time E Min =6,E Mout =12, the service time variances for ETC lane entry and exit are D respectively. Eout =0.5, D Ein =0.3, mean service time E Ein =E Eout =1, a M a is 0.003. E It is 0.016. Assume the previous time interval q... d (k-1) is 3000, calculate r(k) = c a -q d (k-1)=7000pcu / h, λ Min =0.139, λ Mout =0.139, λ Ein =0.083, λ Eout =0.111

[0147] Using Python, pandas, and numpy libraries, solve the following optimization model using the grid search method:

[0148] min C op +C de

[0149]

[0150] N Min N Ein N Mout N Eout ∈N*

[0151] N E +N M +N ED +N MD ≤N T

[0152]

[0153]

[0154] Solving for N, we can obtain the result. Min =1, N Ein =1, N Mout =4, N Eout The optimal solution is obtained when = 2.

[0155] Step S4: Send the solution results to the toll station for execution. Add dynamic lane indication boards 100m and 50m in front of the toll station to help drivers change lanes in time.

[0156] The present invention also provides a port freight channel toll station lane configuration system considering capacity control, comprising:

[0157] The data acquisition module is used to acquire traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances.

[0158] The strategy judgment module is used to determine whether to set a dynamic lane configuration strategy based on traffic flow data and downstream road capacity data. If so, it will enter the toll station lane configuration optimization model construction module to execute; otherwise, it will not set a dynamic lane configuration strategy.

[0159] The toll station lane configuration optimization model building module is used to establish a toll station lane configuration optimization model based on the toll station's traffic flow data and road capacity data, with the optimization objective of minimizing the operating cost and total vehicle delay cost of the freight transport corridor toll station. It also adds constraints to the toll station lane configuration optimization model for the freight transport highway.

[0160] The toll station lane configuration strategy solution module is used to iteratively solve the toll station lane configuration optimization model based on real-time traffic flow data, road capacity data, and the distribution of lanes of various types and directions, to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

[0161] While the present invention has been described above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims. A method and system for configuring lanes at toll stations in port area freight transport corridors, taking capacity control into account.

Claims

1. A method for configuring toll lanes at port freight corridors considering capacity control, characterized in that, Includes the following steps: S1. Obtain traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances; S2. Based on traffic flow data and downstream road capacity data, determine whether to set a dynamic lane configuration strategy. If yes, proceed to step S3; otherwise, do not set a dynamic lane configuration strategy. This includes the following sub-steps: S201. Establish a database: containing traffic flow data and basic road parameters for the freight transport corridor connecting the toll station to the port. S202. Calculate the non-uniformity coefficients for manual toll lane entry, manual toll lane exit, ETC lane entry, and ETC lane exit. As shown in the following formula: ， ， ， ， In the formula, This represents the standard deviation of the hourly traffic intensity as a percentage of the total traffic flow. The intensity of vehicles entering the collection and distribution channel from the manual toll lane. The intensity of vehicles entering the collection and distribution channel from the manual toll lane. To measure the intensity of vehicles entering the ETC (Electronic Toll Collection) and distribution channels. The intensity of oncoming vehicles entering the ETC access lane; S203, Set configuration parameter D: , If satisfied If n is the lower threshold and m is the upper threshold, then no dynamic lane configuration strategy is set. Otherwise, set the dynamic lane configuration strategy and proceed to step S3; S3. Based on toll station traffic flow and road capacity data, and with the optimization objective of minimizing the operating cost and total vehicle delay cost of toll stations on freight transport corridors, an optimization model for toll station lane configuration is established for freight transport highways, and constraints are added. The constraints include: (1) Capacity constraint: the traffic flow allowed through the toll station shall not exceed the capacity of the main line. ， This refers to the number of lanes from the ETC lane to the access road. This refers to the number of lanes for vehicles entering the distribution and collection channel from the manual toll lane. To calculate the regulation rate, The calculation formula is as follows: , This represents the actual traffic capacity downstream of the ramp. This represents the upstream traffic demand of the ramp in the previous time period; (2) Positive integer constraint: the number of all lanes is a positive integer. ， This refers to the number of ETC lanes that exit the access road lanes; This refers to the number of lanes that manually toll lanes exit the access road; (3) Total number of lanes constraint: The total number of all lanes shall not exceed the number of two-way lanes allowed by the road alignment. ， Indicates the number of lanes allowed in both directions for the road alignment; (4) Ensure the capacity of off-ramp lanes; the combined capacity of ETC and MTC lanes exceeds the oncoming traffic intensity to avoid mainline congestion: ， ， In the formula, Average service time for vehicles leaving the collection and distribution channel from the manual toll lane. Average service time for vehicles entering the collection and distribution channel from the ETC lane; S4. Based on real-time traffic flow data, road capacity data, and lane distribution of various types and directions, iteratively solve the toll station lane configuration optimization model to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

2. The method for configuring toll lanes at port freight corridors considering capacity control according to claim 1, characterized in that, In step S1, the traffic flow of vehicles coming from upstream of the entrance toll station and upstream of the exit toll station by vehicle type is converted into traffic flow data according to the preset conversion factor; The capacity of the downstream road of the mainline at the highway toll station entrance is calculated based on the number of lanes and the maximum hourly traffic volume.

3. The method for configuring toll lanes at port freight corridors considering capacity control according to claim 1, characterized in that, In step S3, the operating cost of the toll station for the freight transport corridor is calculated as follows: , In the formula, To open one MTC route, Cost of opening one ETC lane; The total vehicle delay cost corresponding to the toll stations on the freight transport corridor is calculated as follows: ， In the formula, The average queuing delay for vehicles entering the distribution channel from the manual toll lane. The average queuing delay for vehicles leaving the collection and distribution channel from the manual toll lane. This refers to the average queuing delay for vehicles entering the collection and distribution channel via the ETC lane. Average queuing delay for vehicles leaving the ETC lane. To avoid wasting time and money.

4. The method for configuring toll lanes at port freight corridors considering capacity control, as described in claim 3, is characterized in that... The optimization model for toll station lane configuration in step S3 is as follows: 。 5. A method for configuring toll lanes at port freight corridors considering capacity control, as described in claim 4, is characterized in that... , , , Calculate the following formulas respectively: ， ， , , in, The service time variance for vehicles entering the collection and distribution channel from the manual toll lane. The service time variance for vehicles leaving the collection and distribution channel from the manual toll lane. The service time variance for vehicles entering the collection and distribution channel from the ETC lane. Service time variance for vehicles leaving the collection and distribution channel from the ETC lane. The average service time for vehicles entering the collection and distribution channel from the manual toll lane.

6. A lane configuration system for toll stations in port freight corridors considering capacity control, characterized in that, include: The data acquisition module is used to acquire traffic flow data of vehicles coming from upstream of highway entrance toll stations and exit toll stations, as well as road capacity data of the main line downstream of highway toll station entrances. The strategy determination module is used to determine whether to set a dynamic lane configuration strategy based on traffic flow data and downstream road capacity data. If so, it proceeds to the toll station lane configuration optimization model construction module for execution; otherwise, it does not set a dynamic lane configuration strategy. The strategy determination module is configured to execute the following steps: S201. Establish a database: containing traffic flow data and basic road parameters for the freight transport corridor connecting the toll station to the port. S202. Calculate the non-uniformity coefficients for manual toll lane entry, manual toll lane exit, ETC lane entry, and ETC lane exit. As shown in the following formula: , ， ， ， In the formula, This represents the standard deviation of the hourly traffic intensity as a percentage of the total traffic flow. The intensity of vehicles entering the collection and distribution channel from the manual toll lane. The intensity of vehicles entering the collection and distribution channel from the manual toll lane. To measure the intensity of vehicles entering the ETC (Electronic Toll Collection) and distribution channels. The intensity of oncoming vehicles entering the ETC access lane; S203, Set configuration parameter D: , If satisfied If n is the lower threshold and m is the upper threshold, then no dynamic lane configuration strategy is set. Otherwise, set a dynamic lane configuration strategy and execute it in the toll station lane configuration optimization model building module; The toll station lane configuration optimization model building module is used to establish a toll station lane configuration optimization model based on toll station traffic flow data and road capacity data, with the optimization objective of minimizing the operating cost and total vehicle delay cost of toll stations on freight transport corridors. The module also includes constraints, specifically: (1) Capacity constraint: the traffic flow allowed through the toll station shall not exceed the capacity of the main line. ， This refers to the number of lanes from the ETC lane to the access road. This refers to the number of lanes for vehicles entering the distribution and collection channel from the manual toll lane. To calculate the regulation rate, The calculation formula is as follows: , This represents the actual traffic capacity downstream of the ramp. This represents the upstream traffic demand of the ramp in the previous time period; (2) Positive integer constraint: the number of all lanes is a positive integer. ， This refers to the number of ETC lanes that exit the access road lanes; This refers to the number of lanes that manually toll lanes exit the access road; (3) Total number of lanes constraint: The total number of all lanes shall not exceed the number of two-way lanes allowed by the road alignment. ， Indicates the number of lanes allowed in both directions for the road alignment; (4) Ensure the capacity of off-ramp lanes; the combined capacity of ETC and MTC lanes exceeds the oncoming traffic intensity to avoid mainline congestion: ， ， In the formula, Average service time for vehicles leaving the collection and distribution channel from the manual toll lane. Average service time for vehicles entering the collection and distribution channel from the ETC lane; The toll station lane configuration strategy solution module is used to iteratively solve the toll station lane configuration optimization model based on real-time traffic flow data, road capacity data, and the distribution of lanes of various types and directions, to obtain the configuration strategy for dividing the entrance lanes, exit lanes, MTC lanes, and ETC lanes.

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