A lane opening and closing optimization method for a high-speed toll station based on an ETC and MTC mixed lane

Abstract

The application discloses a lane opening and closing optimization method for a high-speed toll station based on an ETC and MTC mixed lane, and comprises the following steps: step one, obtaining toll station operation data, extracting the total lane number and service threshold, and generating a toll operation record; step two, dividing ETC vehicle records and MTC vehicle records according to transaction media, and generating classified statistical records; step three, calculating ETC arrival rates, MTC arrival rates, ETC service rates and MTC service rates; step four, constructing a double-parallel multi-service counter queuing evaluation model, and generating queuing evaluation records; step five, forming ETC occupancy intensity and MTC occupancy intensity, and generating demand configuration records; step six, screening efficiency combinations; step seven, determining saving combinations; and step eight, outputting opening and closing results. The application improves the quantitative nature, traffic efficiency and resource saving capacity of the mixed toll lane opening and closing.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a method for optimizing the opening and closing of highway toll station lanes based on ETC and MTC hybrid lanes. Background Technology

[0002] With the expansion of the highway network and the increasing demand for refined toll station operations, lane opening and closing optimization technology for ETC and MTC hybrid tolling scenarios has received widespread attention. Current toll station lane configurations mainly rely on manual experience, historical traffic patterns, or simple vehicle ratio analysis for judgment, but in practical applications, the following problems commonly exist:

[0003] ETC vehicles and MTC vehicles differ significantly in terms of transaction medium, travel time, and single-lane service capacity. Existing methods tend to merge the two types of vehicles in statistics, making it difficult to accurately match the number of lanes opened with the actual service load. There is a lack of a unified standardization mechanism among toll station transaction data, lane data, and time period data, making it difficult to establish a corresponding calculation relationship between vehicle arrival rate and lane service rate in the same time period. Some methods rely on short-term traffic prediction, simulation platforms, and weighted evaluation models, which are complex to calibrate and have high implementation costs. If only the minimum queuing time is pursued during low-traffic periods, it is easy to cause long-term redundant lane opening. If the number of lanes opened is simply reduced during medium-to-high-traffic periods, it may cause the service intensity of ETC or MTC branches to be too high, resulting in an increase in average queuing time and a decrease in toll station traffic efficiency.

[0004] Therefore, how to provide a method for optimizing the opening and closing of highway toll station lanes based on ETC and MTC hybrid lanes is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] One objective of this invention is to propose an optimization method for lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes. This invention fully utilizes toll operation data and a dual-parallel multi-service station queuing evaluation model to calculate the arrival rate, service rate, service intensity, and queuing time for ETC vehicles and MTC vehicles respectively. It also combines demand configuration records to complete the selection of efficiency combinations and cost-saving combinations, which has the advantages of quantitative lane configuration, high accuracy of queuing evaluation, and good resource saving effect during low-traffic periods.

[0006] An optimization method for lane opening and closing at a highway toll station based on a hybrid ETC and MTC lane, according to an embodiment of the present invention, includes the following steps:

[0007] Step 1: Obtain toll station operation data, extract the total number of lanes and service thresholds, organize the transaction field and lane field and segment the time period to generate toll operation records;

[0008] Step 2: Divide the toll collection operation records into ETC vehicle records and MTC vehicle records according to the transaction medium, and generate classified statistical records by counting the traffic volume;

[0009] Step 3: Calculate the ETC arrival rate and MTC arrival rate from the classification statistics records, and extract the unit throughput from the toll operation records and generate the ETC service rate and MTC service rate after anomaly removal and scale conversion;

[0010] Step 4: Couple arrival rate and service rate, introduce the variable of number of open lanes, construct a dual parallel multi-server queuing evaluation model, calculate service intensity and queuing time to generate queuing evaluation records;

[0011] Step 5: Project the arrival rate using service capacity as a scale to form ETC occupancy intensity and MTC occupancy intensity, and generate demand configuration records by calibrating the total scale and bias direction;

[0012] Step 6: Generate a candidate configuration set based on the total number of lanes and service intensity, and select the efficiency combination with the minimum queuing time by combining queuing evaluation records and demand configuration records;

[0013] Step 7: Filter the qualified configuration records from the candidate configuration set whose queuing time meets the service threshold, and determine the cost-saving combination according to the principle of the minimum number of lanes opened;

[0014] Step 8: Output the saving combination if a saving combination exists, and output the efficiency combination if no saving combination exists, forming the opening and closing results containing the number of ETC openings, the number of MTC openings, and the number of closings.

[0015] Optionally, step one specifically includes:

[0016] Extract transaction fields, lane fields, time period fields, and threshold fields from the toll station operation data. Standardize the transaction time format and organize the transaction medium code for the transaction fields. Verify the lane identification and label the lane type for the lane fields to generate a field-organized record.

[0017] Based on the lane identifier verification results in the field regularization record, the number of available lanes is counted to generate the total number of lanes. Based on the threshold field in the field regularization record, the upper limit of average queuing time is extracted to generate the service threshold.

[0018] Based on the time period field in the field-organized record, establish the analysis time period boundary, and map the transaction field after the transaction time format is unified to the analysis time period boundary to form a time period segmentation record;

[0019] The time period segmentation records, lane type identification results, total number of lanes, and service thresholds are linked and organized according to the toll station identification to generate toll operation records.

[0020] Optionally, step two specifically includes:

[0021] Extract the transaction medium code, transaction time, lane identification, toll station identification and time period identification from the toll operation record. Establish a vehicle type determination table according to the transaction medium code, and map the antenna transaction code to the ETC type and the CPC card transaction code and the hand-torn ticket transaction code to the MTC type.

[0022] Based on the vehicle type determination table, the toll operation records are matched by type. The toll operation records that match the ETC type are classified into the ETC vehicle record, and the toll operation records that match the MTC type are classified into the MTC vehicle record.

[0023] ETC vehicle records are grouped and statistically analyzed according to toll station identification and time period identification to generate ETC traffic volume; MTC vehicle records are grouped and statistically analyzed according to toll station identification and time period identification to generate MTC traffic volume.

[0024] ETC vehicle records, MTC vehicle records, ETC traffic volume, and MTC traffic volume are linked and organized according to toll station identifiers and time period identifiers to generate classified statistical records for use in calculating ETC arrival rate and MTC arrival rate.

[0025] Optionally, step three specifically includes:

[0026] Extract ETC traffic volume, MTC traffic volume, and time period identifier from the classified statistical records. Determine the time period duration from the time period identifier. Calculate the ETC arrival rate by comparing the ETC traffic volume with the time period duration. Calculate the MTC arrival rate by comparing the MTC traffic volume with the time period duration.

[0027] Extract lane identification, lane type calibration results, and transaction time from the toll operation records. Based on the lane identification and lane type calibration results, aggregate the number of vehicles passing through within the same transaction time period to generate ETC unit throughput and MTC unit throughput.

[0028] Based on the historical statistical range corresponding to the lane type calibration results, deviation judgment is made on the ETC unit throughput and MTC unit throughput, abnormal unit throughput exceeding the historical statistical range is removed, and the retained unit throughput is converted to a time scale.

[0029] The ETC unit throughput after time scale conversion is determined as the ETC service rate, and the MTC unit throughput after time scale conversion is determined as the MTC service rate. The ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate are then linked and organized according to the toll station identifier and time period identifier.

[0030] Optionally, step four specifically includes:

[0031] Arrival service parameters are extracted from ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate. The number of ETC lanes opened is used as the service station capacity of the ETC queuing evaluation branch, and the number of MTC lanes opened is used as the service station capacity of the MTC queuing evaluation branch. A dual-parallel multi-service station queuing evaluation model is constructed.

[0032] In the ETC queuing evaluation branch, the ETC arrival rate, ETC service rate, and number of ETC-enabled lanes are used for capacity matching calculation to generate ETC service intensity. In the MTC queuing evaluation branch, the MTC arrival rate, MTC service rate, and number of MTC-enabled lanes are used for capacity matching calculation to generate MTC service intensity.

[0033] The ETC waiting probability is calculated based on the ETC service intensity and the number of ETC lanes in operation, and the ETC queuing time is converted from the ETC waiting probability. Similarly, the MTC waiting probability is calculated based on the MTC service intensity and the number of MTC lanes in operation, and the MTC queuing time is converted from the MTC waiting probability.

[0034] Arrival rate weights are formed based on ETC arrival rate and MTC arrival rate. The arrival rate weights are then used to weight and aggregate the ETC queuing time and MTC queuing time to generate a comprehensive queuing time. ETC service intensity, MTC service intensity, ETC queuing time, MTC queuing time and comprehensive queuing time are then linked and organized according to toll station identifiers and time period identifiers to generate a queuing evaluation record.

[0035] Optionally, step five specifically includes:

[0036] The arrival service parameters under the same toll station identifier and the same time period identifier are extracted from ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate. The ETC service rate is determined as the single lane service capacity of ETC vehicles, and the MTC service rate is determined as the single lane service capacity of MTC vehicles.

[0037] The ETC arrival rate is converted into capacity occupancy based on the ETC service rate to generate ETC occupancy intensity. The MTC arrival rate is converted into capacity occupancy based on the MTC service rate to generate MTC occupancy intensity.

[0038] The total quantity of lane resources is generated by summing the ETC occupancy intensity and MTC occupancy intensity. The difference between the ETC occupancy intensity and MTC occupancy intensity is calculated to generate the bias direction that represents the lane resource bias type.

[0039] The ETC occupancy intensity, MTC occupancy intensity, total volume scale, and bias direction are associated and organized according to the toll station identifier and time period identifier to generate a demand configuration record for screening candidate configuration sets.

[0040] Optionally, step six specifically includes:

[0041] Establish a quantity balance relationship between the number of ETC activated, MTC activated, and deactivated lanes based on the total number of lanes, and form an initial configuration record according to non-negative integer values;

[0042] The number of ETC activations and MTC activations in the initial configuration record are introduced into the dual-parallel multi-server queuing evaluation model to calculate the ETC service strength, MTC service strength and comprehensive queuing time. The initial configuration record in which both ETC service strength and MTC service strength meet the stability condition is retained to generate a candidate configuration set.

[0043] Extract ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction from the demand configuration record. Perform demand adaptation calculation on the number of ETC and MTC enabled in the candidate configuration set to generate configuration adaptation results.

[0044] By combining the overall queuing time and configuration adaptation results in the queuing evaluation records, the candidate configuration set is sorted and filtered, and the candidate configuration with the minimum overall queuing time and configuration adaptation results that meet the bias direction is determined as the efficiency combination.

[0045] Optionally, step seven specifically includes:

[0046] Extract candidate configuration records from the candidate configuration set, match the candidate configuration records with the comprehensive queuing time in the queuing evaluation records, compare the comprehensive queuing time with the service threshold, and generate the threshold comparison result.

[0047] Candidate configuration records whose threshold comparison results do not exceed the service threshold are identified as compliant configuration records, and candidate configuration records whose threshold comparison results exceed the service threshold are removed from the candidate configuration set.

[0048] The number of ETC and MTC activated in the compliance configuration records is summed to generate the total number of activated lanes, and the compliance configuration records are arranged in ascending order of the total number of activated lanes.

[0049] In the qualified configuration record with the minimum total number of open lanes, the saving combination is determined according to the comprehensive queuing time from small to large, and the saving combination is correlated with the number of ETC open, MTC open and closed.

[0050] Optionally, step eight specifically includes:

[0051] The integrity of the savings combination is determined. A savings combination existence mark is generated when the savings combination is associated with the number of ETC activations, MTC activations, and deactivations. A savings combination missing mark is generated when the savings combination is not associated with the number of ETC activations, MTC activations, and deactivations.

[0052] When a saving combination is marked, the saving combination is identified as the target open / closed combination; when a saving combination is missing a mark, the efficiency combination is identified as the target open / closed combination.

[0053] Extract the number of ETC activated, MTC activated, and deactivated from the target activation / deactivation combination, and verify the consistency of the number of ETC activated, MTC activated, and deactivated with the total number of lanes;

[0054] After the quantity consistency verification is passed, the target opening and closing combination, toll station identifier, time period identifier, and comprehensive queuing time are linked and organized to form the opening and closing result including the number of ETC openings, the number of MTC openings, and the number of closings.

[0055] The beneficial effects of this invention are:

[0056] This invention acquires toll station operation data and generates toll operation records, integrating transaction, lane, time period, and threshold fields into a unified processing chain. This allows toll station identifiers, time period identifiers, lane identifiers, and transaction medium codes to be associated within the same calculation scope, avoiding configuration deviations caused by reliance on manual experience and simple vehicle ratio judgments in traditional lane opening and closing management. The toll operation records are divided into ETC vehicle records and MTC vehicle records using a vehicle type determination table. ETC arrival rates and MTC arrival rates are then calculated from the categorized statistical records. Unit throughput is extracted from the toll operation records to generate ETC service rates and MTC service rates, establishing a correspondence between vehicle arrival scale and single-lane service capacity. This accurately reflects the differences between ETC and MTC vehicles in terms of transaction methods, traffic efficiency, and service load, thus providing a more reliable data foundation for lane opening and closing optimization.

[0057] This invention further employs a dual-parallel multi-server queuing evaluation model, incorporating the variables of the number of ETC-enabled lanes and the number of MTC-enabled lanes into the ETC queuing evaluation branches and MTC queuing evaluation branches, respectively. It calculates ETC service intensity, MTC service intensity, ETC queuing time, MTC queuing time, and overall queuing time, enabling the candidate configuration set to complete queuing efficiency evaluation under stable conditions. By projecting arrival rates onto service capacity as a scale to form ETC and MTC occupancy intensities, and using total volume scale and bias direction to generate demand configuration records, lane configuration not only considers queuing time but also reflects the overall demand for lane resources and the bias towards ETC / MTC resources. Through progressive screening of efficiency combinations and cost-saving combinations, it prioritizes lower overall queuing time during high-traffic periods, reduces the total number of enabled lanes while meeting service thresholds during low-traffic periods, and outputs efficiency combinations when cost-saving combinations are unavailable, thus balancing traffic efficiency, resource conservation, and the executability of opening and closing results. Attached Figure Description

[0058] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0059] Figure 1 This is a flowchart of a method for optimizing the opening and closing of highway toll stations based on a hybrid ETC and MTC lane proposed in this invention.

[0060] Figure 2 This is a schematic diagram of the dual-parallel multi-service queue evaluation model structure for a highway toll station lane opening and closing optimization method based on ETC and MTC hybrid lanes proposed in this invention. Detailed Implementation

[0061] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0062] refer to Figures 1-2 A method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes includes the following steps:

[0063] Step 1: Obtain toll station operation data, extract the total number of lanes and service thresholds, organize the transaction field and lane field and segment the time period to generate toll operation records;

[0064] Step 2: Divide the toll collection operation records into ETC vehicle records and MTC vehicle records according to the transaction medium, and generate classified statistical records by counting the traffic volume;

[0065] Step 3: Calculate the ETC arrival rate and MTC arrival rate from the classification statistics records, and extract the unit throughput from the toll operation records and generate the ETC service rate and MTC service rate after anomaly removal and scale conversion;

[0066] Step 4: Couple arrival rate and service rate, introduce the variable of number of open lanes, construct a dual parallel multi-server queuing evaluation model, calculate service intensity and queuing time to generate queuing evaluation records;

[0067] Step 5: Project the arrival rate using service capacity as a scale to form ETC occupancy intensity and MTC occupancy intensity, and generate demand configuration records by calibrating the total scale and bias direction;

[0068] Step 6: Generate a candidate configuration set based on the total number of lanes and service intensity, and select the efficiency combination with the minimum queuing time by combining queuing evaluation records and demand configuration records;

[0069] Step 7: Filter the qualified configuration records from the candidate configuration set whose queuing time meets the service threshold, and determine the cost-saving combination according to the principle of the minimum number of lanes opened;

[0070] Step 8: Output the saving combination if a saving combination exists, and output the efficiency combination if no saving combination exists, forming the opening and closing results containing the number of ETC openings, the number of MTC openings, and the number of closings.

[0071] In this embodiment, step one specifically includes:

[0072] The system extracts transaction, lane, time period, and threshold fields from toll station operation data. It standardizes the format of transaction time in the transaction field to bring transaction times from different sources into the same time expression scale. It encodes and organizes the transaction medium to form identifiable medium codes for antenna transactions, CPC card transactions, and hand-torn ticket transactions. It verifies the validity of lane identifiers in the lane field and generates lane type calibration results according to lane passage attributes. It combines the results of standardized transaction time format, transaction medium coding, lane identifier verification, and lane type calibration to generate a field-organized record.

[0073] Invalid lane signs are filtered out based on the lane sign verification results in the field regularization record. The number of lane signs that pass the verification is counted to obtain the total number of lanes participating in the lane opening and closing calculation. Then, the upper limit of average queuing time is extracted based on the threshold field in the field regularization record. The upper limit of average queuing time is used as the service level constraint boundary to generate the service threshold.

[0074] Based on the time period field in the field regularization record, the start and end boundaries of the analysis time period are determined. The transaction time with the unified format is mapped to the analysis time period boundary one by one, so that each transaction field forms a correspondence between the toll station identifier, lane identifier and analysis time period, and a time period segmentation record is generated.

[0075] The time period segmentation records, lane type calibration results, total number of lanes and service thresholds are linked and organized according to the toll station identification, so that the transaction fields, lane fields, analysis time periods, total number of lanes and service thresholds under the same toll station identification form a unified calculation object, generating toll operation records that can support the division of ETC vehicle records and MTC vehicle records.

[0076] In this embodiment, step two specifically includes:

[0077] Extract the transaction medium code, transaction time, lane identifier, toll station identifier, and time period identifier from the toll operation record so that each toll operation record has a field base that can be used for vehicle type determination and time period aggregation. Then, establish a vehicle type determination table according to the transaction medium code, map the antenna transaction code to the ETC type, and map the CPC card transaction code and the hand-torn ticket transaction code to the MTC type.

[0078] Based on the vehicle type determination table, the toll operation records are matched by type. When the transaction medium code and the ETC type mapping relationship are consistent, the toll operation record is classified into the ETC vehicle record. When the transaction medium code and the MTC type mapping relationship are consistent, the toll operation record is classified into the MTC vehicle record, so that the toll operation records are separated into two types of vehicle records according to the toll collection method.

[0079] ETC vehicle records are grouped according to toll station identification and time period identification, so that ETC vehicle records under the same toll station identification and the same time period identification are included in the same statistical range. The number of ETC vehicle records within the statistical range is accumulated to generate ETC traffic volume. Then, MTC vehicle records are grouped according to toll station identification and time period identification, and the number of MTC vehicle records within the group is accumulated to generate MTC traffic volume.

[0080] ETC vehicle records, MTC vehicle records, ETC traffic volume, and MTC traffic volume are linked and organized according to toll station identifiers and time period identifiers, so that vehicle records and traffic volumes under the same toll station identifier and the same time period identifier are correlated, generating classified statistical records for use in calculating ETC arrival rate and MTC arrival rate.

[0081] In this embodiment, step three specifically includes:

[0082] Extract toll station identifiers, ETC traffic volume, MTC traffic volume, and time period identifiers from the classification statistics records. The start and end times of the corresponding analysis time period are determined by the time period identifiers. The time difference between the end time and the start time is used as the time period length. The ETC traffic volume is divided by the time period length to obtain the ETC arrival rate, and the MTC traffic volume is divided by the time period length to obtain the MTC arrival rate.

[0083] The system extracts lane identification, lane type calibration results, and transaction time from the toll operation records. It distinguishes different toll lanes according to lane identification, and distinguishes ETC lanes and MTC lanes according to lane type calibration results. It then categorizes vehicle passage records with transaction times within the same time period into the corresponding lane type range, and accumulates the number of vehicles passing through the corresponding lane type range to generate ETC unit passage volume and MTC unit passage volume.

[0084] Based on the historical statistical range corresponding to the lane type calibration results, deviation judgments are made for ETC unit throughput and MTC unit throughput respectively. Unit throughput that exceeds the historical statistical range is removed as abnormal unit throughput. The retained unit throughput is converted from minute scale to hour scale to obtain the time-scale converted ETC unit throughput and time-scale converted MTC unit throughput.

[0085] The ETC unit throughput after time scale conversion is determined as the ETC service rate, and the MTC unit throughput after time scale conversion is determined as the MTC service rate. The ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate are linked and organized according to the toll station identifier and time period identifier, so that the arrival rate and service rate under the same toll station identifier and the same time period identifier form a matching relationship.

[0086] This invention calculates ETC arrival rate and MTC arrival rate from classified statistical records, and extracts ETC unit throughput and MTC unit throughput from toll operation records. This establishes a corresponding calculation relationship between vehicle arrival scale and lane service capacity under the same toll station identifier and the same time period identifier, avoiding data mixing between different analysis periods that could cause arrival rate distortion. By aggregating vehicle throughput according to lane identifier and lane type calibration results, it can distinguish the difference in unit time throughput capacity between ETC lanes and MTC lanes, avoiding service rate deviation caused by merging the service capacity estimates of the two types of lanes. By using historical statistical ranges to determine deviations in unit throughput and removing abnormal unit throughput before performing time scale conversion, it can reduce the impact of sudden abnormal transactions and local data loss on service rate calculation. By associating and organizing ETC arrival rate, MTC arrival rate, ETC service rate, and MTC service rate according to toll station identifier and time period identifier, it can provide consistent arrival service parameters for the dual-parallel multi-service station queuing evaluation model, thereby improving the accuracy of service intensity calculation, queuing time calculation, and lane opening and closing optimization results.

[0087] In this embodiment, step four specifically includes:

[0088] Arrival service parameters are extracted from the ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate after being associated and organized according to toll station identifiers and time period identifiers. The variable of the number of ETC open lanes is configured as the service station capacity that can participate in ETC vehicle service in the ETC queuing evaluation branch, and the variable of the number of MTC open lanes is configured as the service station capacity that can participate in MTC vehicle service in the MTC queuing evaluation branch. This enables the ETC queuing evaluation branch and the MTC queuing evaluation branch to form a dual parallel multi-service station queuing evaluation model under the same toll station identifier and the same time period identifier.

[0089] In the ETC queuing evaluation branch, the ETC service rate is multiplied by the variable of the number of ETC lanes open to form the ETC service capacity. Then, the ETC arrival rate is matched with the ETC service capacity to generate the ETC service intensity. In the MTC queuing evaluation branch, the MTC service rate is multiplied by the variable of the number of MTC lanes open to form the MTC service capacity. Then, the MTC arrival rate is matched with the MTC service capacity to generate the MTC service intensity.

[0090] The probability of an ETC vehicle entering the waiting queue is calculated based on the ETC service intensity and the number of ETC lanes open. The probability of an ETC vehicle entering the waiting queue is converted into ETC queuing time by combining the ETC service rate and the number of ETC lanes open. The probability of an MTC vehicle entering the waiting queue is calculated based on the MTC service intensity and the number of MTC lanes open. The probability of an MTC vehicle entering the waiting queue is converted into MTC queuing time by combining the MTC service rate and the number of MTC lanes open.

[0091] Arrival rate weights are formed by the proportion of ETC arrival rate and MTC arrival rate under the same time period identifier. The arrival rate weights are used to weight and aggregate the ETC queuing time and MTC queuing time to generate a comprehensive queuing time. The ETC service intensity, MTC service intensity, ETC queuing time, MTC queuing time and comprehensive queuing time are associated and organized according to the toll station identifier and time period identifier to generate a queuing evaluation record.

[0092] This invention incorporates ETC arrival rate, MTC arrival rate, ETC service rate, and MTC service rate into the ETC queuing evaluation branch and the MTC queuing evaluation branch, respectively, and uses the number of ETC and MTC open lanes as service station capacity variables. This establishes a corresponding calculation relationship between the two toll collection methods in terms of vehicle arrival intensity, single-lane service capacity, and number of open lanes. By generating ETC and MTC service intensity through capacity matching calculations, the load levels of the two queuing branches under different lane configurations can be determined, avoiding the neglect of service capacity differences caused by simply relying on vehicle proportions for lane allocation. ETC and MTC queuing times are converted from waiting probabilities, and a comprehensive queuing time is generated according to the arrival rate weight, enabling the queuing evaluation record to simultaneously reflect the impact of ETC and MTC vehicles on the overall waiting level of the toll station. By associating and organizing service intensity, branch queuing time, and comprehensive queuing time according to toll station and time segment identifiers, a unified evaluation basis can be provided for candidate configuration set generation, efficiency combination screening, and cost-saving combination judgment, thereby improving the quantification, interpretability, and operational adaptability of lane opening and closing results.

[0093] In this embodiment, step five specifically includes:

[0094] From ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate, arrival service parameters belonging to the same calculation range are extracted according to toll station identification and time period identification. ETC service rate is used as the service capacity of ETC vehicles on a single ETC lane, and MTC service rate is used as the service capacity of MTC vehicles on a single MTC lane, so that the vehicle arrival scale and single lane processing capacity are included in the same calculation range.

[0095] Dividing the ETC arrival rate by the ETC service rate yields the capacity occupancy result of ETC vehicles on ETC lane resources, and the capacity occupancy result is determined as the ETC occupancy intensity. Dividing the MTC arrival rate by the MTC service rate yields the capacity occupancy result of MTC vehicles on MTC lane resources, and the capacity occupancy result is determined as the MTC occupancy intensity.

[0096] The ETC occupancy intensity and MTC occupancy intensity are accumulated to obtain a total scale reflecting the overall demand of lane resources at the toll station in the same period. Then, the difference between the ETC occupancy intensity and the MTC occupancy intensity is calculated. Based on the positive or negative state of the difference, it is determined whether the lane resource demand is biased towards the ETC side or the MTC side, thus generating the bias direction.

[0097] The ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction are linked and organized according to the toll station identifier and time period identifier, so that the lane resource occupancy scale and lane resource bias type under the same toll station identifier and the same time period identifier are unified into a record, and a demand configuration record is generated for the candidate configuration set to be screened.

[0098] This invention converts ETC arrival rate into capacity occupancy based on ETC service rate, and MTC arrival rate into capacity occupancy based on MTC service rate. This transforms vehicle arrival scale from solely relying on vehicle quantity for lane configuration judgment into ETC and MTC occupancy intensity that matches the service capacity of a single lane. By using a total quantity scale to characterize the overall demand for lane resources under the same toll station and time period, it provides a quantitative basis for determining whether the number of open lanes is sufficient for the candidate configuration set. By using the bias direction to characterize whether lane resource demand is biased towards the ETC side or the MTC side, it avoids weakening the service capacity difference caused by configuring lanes solely based on vehicle proportion. By organizing ETC occupancy intensity, MTC occupancy intensity, total quantity scale, and bias direction into a demand configuration record, the candidate configuration set screening process is simultaneously constrained by the resource demand scale and resource bias type, thereby improving the accuracy and interpretability of efficiency combination screening and cost-saving combination judgment.

[0099] In this embodiment, step six specifically includes:

[0100] Based on the total number of lanes, establish a quantitative balance relationship between the number of ETC activated, MTC activated, and closed lanes, so that the sum of the number of ETC activated, MTC activated, and closed lanes equals the total number of lanes. Then, combine the number of ETC activated, MTC activated, and closed lanes in sequence according to non-negative integer values ​​to form an initial configuration record that can participate in lane opening and closing evaluation.

[0101] The number of ETC activations and the number of MTC activations in the initial configuration record are introduced into the dual-parallel multi-server queuing evaluation model. This allows the number of ETC activations to participate in the calculation of ETC service intensity, and the number of MTC activations to participate in the calculation of MTC service intensity. Based on the ETC service intensity, MTC service intensity, ETC queuing time, and MTC queuing time, a comprehensive queuing time is formed. Then, the initial configuration records in which both ETC service intensity and MTC service intensity meet the stability condition are retained to generate a candidate configuration set.

[0102] Extract ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction from the demand configuration record. Compare the number of ETC enabled lanes in the candidate configuration set with the corresponding ETC occupancy intensity and the number of MTC enabled lanes in the candidate configuration set with the corresponding MTC occupancy intensity. Combine the total scale to determine whether the total number of enabled lanes in the candidate configuration set meets the overall lane resource demand and generate configuration adaptation results.

[0103] Combining the overall queuing time and configuration adaptation results in the queuing evaluation records, the candidate configuration set is sorted from smallest to largest based on the overall queuing time. From the sorting results, candidate configurations whose configuration adaptation results satisfy the bias direction are selected. The candidate configuration with the smallest overall queuing time and whose configuration adaptation results satisfy the bias direction is determined as the efficiency combination.

[0104] This invention establishes a quantitative balance between the number of ETC (Electronic Toll Collection) activated lanes, the number of MTC (Mechanical Toll Collection) activated lanes, and the number of lanes closed by using the total number of lanes. This ensures that the candidate configuration set is formed within the total lane resources, preventing the number of lanes activated and closed from exceeding the actual available range. By introducing the initial configuration records into a dual-parallel multi-server queuing evaluation model and filtering out unstable configurations based on ETC and MTC service strengths, the candidate configuration set has a foundation for queuing stability. By generating configuration adaptation results using ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction, the efficiency combination selection is based not only on the overall queuing time but also on the resource demand bias of the ETC and MTC sides. By selecting the candidate configuration with the minimum overall queuing time and configuration adaptation results that satisfy the bias direction from the candidate configuration set, the matching degree between the efficiency combination and the actual vehicle structure and lane service capacity can be improved, thereby enhancing the traffic efficiency and configuration rationality of the lane activation and closure optimization results.

[0105] In this embodiment, step seven specifically includes:

[0106] Candidate configuration records are extracted one by one from the candidate configuration set. Each candidate configuration record contains the number of ETC activations, MTC activations, and deactivations. The toll station identifier and time period identifier are used as matching indexes to match the candidate configuration records with the comprehensive queuing time in the queuing evaluation records. The comprehensive queuing time is then compared with the service threshold. The comparison results are used to form a threshold comparison result to characterize whether the service level meets the standard.

[0107] Based on the threshold comparison results, candidate configuration records are screened. Candidate configuration records whose overall queuing time does not exceed the service threshold are identified as qualified configuration records. Candidate configuration records whose overall queuing time exceeds the service threshold are removed from the candidate configuration set, so that the remaining qualified configuration records simultaneously meet the service intensity constraint and the service threshold constraint.

[0108] For each compliant configuration record, the number of ETC activations and the number of MTC activations are summed to obtain the total number of activated lanes. The total number of activated lanes is used as the resource utilization evaluation metric. The compliant configuration records are then arranged in ascending order of the total number of activated lanes, so that compliant configuration records with a smaller total number of activated lanes have priority in the resource-saving combination judgment.

[0109] Within the range of compliant configuration records with the smallest total number of open lanes, further filtering is performed in ascending order of comprehensive queuing time. The compliant configuration record with the smallest comprehensive queuing time is determined as the saving combination. The saving combination is then correlated with the number of ETC, MTC, and deactivated lanes to ensure that the saving combination meets the service threshold requirements while corresponding to fewer open lanes.

[0110] This invention matches candidate configuration records with the comprehensive queuing time in queuing evaluation records and compares the comprehensive queuing time with a service threshold. This allows the candidate configuration set to complete the qualification screening according to service level constraints, preventing lane configurations with comprehensive queuing times exceeding the service threshold from entering the saving combination judgment process. By summing the number of ETC and MTC activated in the qualified configuration records to form the total number of activated lanes, the resource occupancy level can be sorted with a clear value, avoiding excessive lane opening during low-traffic periods due to only aiming for the minimum queuing time. By determining the saving combination again based on the comprehensive queuing time within the qualified configuration record range with the minimum number of activated lanes, the saving combination simultaneously meets the service threshold requirements and the requirement to reduce the number of activated lanes. By associating and organizing the saving combination with the number of ETC activated, MTC activated, and deactivated lanes, it can provide a directly executable lane number configuration relationship for the opening and closing results, thereby improving the resource saving capacity of toll stations during low-traffic periods and the service level maintenance capacity during medium- and high-traffic periods.

[0111] In this embodiment, step eight specifically includes:

[0112] The completeness of the saving combination is determined by first checking whether the saving combination carries the number of ETC activations, MTC activations, and deactivations, and then verifying whether the source of the saving combination is a compliant configuration record. When the saving combination carries the number of ETC activations, MTC activations, and deactivations and the source is a compliant configuration record, it means that the saving selection process has obtained a configuration that meets the service threshold and the principle of the minimum number of activated lanes, and a saving combination existence mark is generated. When the saving combination does not carry the number of ETC activations, MTC activations, and deactivations, it means that the compliant configuration record has failed to form a saving combination, and a saving combination missing mark is generated.

[0113] When a marker exists for generating a cost-saving combination, the cost-saving combination is identified as the target start-stop combination, and the target start-stop combination adopts a configuration with fewer open lanes under service threshold constraints. When a marker is missing for generating a cost-saving combination, the efficiency combination is identified as the target start-stop combination, and the target start-stop combination adopts a configuration with the minimum overall queuing time, so that the queuing efficiency target of the toll station is not lost when a cost-saving combination cannot be formed.

[0114] Extract the number of ETC activations, MTC activations, and deactivations from the target activation / deactivation combination. Sum the number of ETC activations, MTC activations, and deactivations to obtain the total activation / deactivation count. Then, compare the total activation / deactivation count with the total number of lanes. If the total activation / deactivation count equals the total number of lanes, the consistency check is considered passed. If the total activation / deactivation count does not equal the total number of lanes, stop generating the activation / deactivation result.

[0115] After the quantity consistency verification is passed, the target start-up and closing combination is associated with the toll station identifier, time period identifier, and comprehensive queuing time to form an executable lane start-up and closing scheme under the same toll station identifier and the same time period identifier. The number of ETC activations, MTC activations, and deactivations in the target start-up and closing combination are used as the output content of the start-up and closing result.

[0116] Example 1: To verify the feasibility of this invention in practice, it was applied to the opening and closing management scenario of a mixed ETC and MTC lane at the entrance plaza of a highway toll station. The entrance plaza has four valid lanes. In operation, a fixed opening method has long been used as a comparison scheme: two lanes are open for ETC, two for MTC, and none are closed, maintaining the same lane configuration during off-peak, off-peak, and peak periods. The advantage of this comparison scheme is its simplicity, but it does not utilize toll collection data to differentiate between ETC and MTC vehicles in terms of arrival and service rates, nor does it determine whether redundant lanes exist during off-peak periods based on service thresholds. Therefore, it easily leads to a waste of equipment, personnel, and monitoring resources during periods of low vehicle traffic.

[0117] In this embodiment, the service threshold is set to a total queuing time of no more than 1.0s. Toll station operation data is processed through transaction field normalization, lane field normalization, and time period segmentation to generate toll operation records. These records are then categorized into ETC vehicle records and MTC vehicle records based on the transaction medium. Vehicle arrival rates are calculated using classified statistical records. Unit throughput is extracted from the toll operation records, and anomaly removal and scaling are performed, resulting in an ETC service rate of 1260 vehicles / h and an MTC service rate of 720 vehicles / h. During off-peak hours, the ETC arrival rate is 18 vehicles / h and the MTC arrival rate is 21 vehicles / h; during off-peak hours, the ETC arrival rate is 464 vehicles / h and the MTC arrival rate is 278 vehicles / h; and during peak hours, the ETC arrival rate is 997 vehicles / h and the MTC arrival rate is 297 vehicles / h. This indicates that the total traffic volume is relatively small during off-peak hours, there is stable demand for both ETC and MTC vehicles during off-peak hours, and the ETC vehicle arrival rate increases significantly during peak hours. If a single empirical rule is still applied, it will be difficult to balance resource conservation during off-peak hours with queuing efficiency during peak hours.

[0118] This invention couples ETC arrival rate, MTC arrival rate, ETC service rate, and MTC service rate into a dual-parallel multi-server queuing evaluation model, and introduces variables for the number of ETC and MTC open lanes to form a candidate configuration set for different numbers of ETC, MTC, and closed lanes. Under the constraint of four total lanes, the candidate configuration set includes six configuration relationships: 1 / 1 / 2, 1 / 2 / 1, 2 / 1 / 1, 2 / 2 / 0, 1 / 3 / 0, and 3 / 1 / 0. The system first calculates the ETC service intensity, MTC service intensity, and comprehensive queuing time corresponding to each candidate configuration. Then, it uses ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction to form a demand configuration record, and combines this with the queuing evaluation record to filter efficiency combinations. Furthermore, the system compares the comprehensive queuing time of the candidate configurations with a 1.0s service threshold. Among the candidate configurations that meet the service threshold, a saving combination is determined according to the principle of minimizing the number of open lanes. If a saving combination is not formed, an efficiency combination is output back, avoiding sacrificing traffic efficiency to pursue closed lanes.

[0119] The comparison scheme in this embodiment is a fixed opening scheme, while the scheme of the present invention is an opening and closing result automatically determined according to the charging operation record, queue evaluation record, and demand configuration record. The comparison results are shown in Table 1:

[0120] Table 1 Comparison of Lane Opening and Closing Benefits Operational phase ETC arrival rate (vehicles / hour) MTC arrival rate (vehicles / hour) Comparison of options (ETC / MTC / Off) The solution of this invention (ETC / MTC / Off) Comparison of overall queuing time (s) for different schemes This invention integrates queuing time (s). Queue length (vehicles) of the system of this invention Lane opening savings off-peak period 18 21 2 / 2 / 0 1 / 1 / 2 0.001 0.100 0.0011 50.0% Off-peak period 464 278 2 / 2 / 0 2 / 2 / 0 0.135 0.135 0.0279 0.0% Peak period 997 297 2 / 2 / 0 2 / 2 / 0 0.460 0.460 0.1652 0.0%

[0121] As shown in Table 1, the comparative scheme uses a fixed 2 / 2 / 0 opening mode in all three operating phases. Although the overall queuing time is lowest in the off-peak phase, opening all four lanes results in significant resource redundancy. With this invention, calculations based on the ETC arrival rate of 18 vehicles / h, the MTC arrival rate of 21 vehicles / h, and the service rates of the two types of lanes in the off-peak phase show that one ETC lane and one MTC lane are sufficient to meet the service threshold requirements. Therefore, the opening / closing result is adjusted to 1 / 1 / 2, with an overall queuing time of 0.100s, still significantly lower than the 1.0s service threshold. Simultaneously closing two lanes achieves a lane opening saving rate of 50.0%. In the off-peak and peak phases, reducing the number of open lanes causes the overall queuing time of the candidate configuration to exceed the service threshold, preventing the formation of a saving combination. This invention automatically outputs the efficiency combination 2 / 2 / 0, keeping the overall queuing time at 0.135s in the off-peak phase and 0.460s in the peak phase. This demonstrates that the present invention does not simply reduce the number of open lanes, but rather saves resources while meeting service thresholds. When vehicle arrival pressure increases, the present invention can revert to an efficiency combination, ensuring that both ETC and MTC vehicles have stable service capabilities, thereby solving the problem that fixed opening and closing schemes cannot simultaneously adapt to low-peak resource saving and peak-peak traffic efficiency.

[0122] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes, characterized in that, Includes the following steps: Step 1: Obtain toll station operation data, extract the total number of lanes and service thresholds, organize the transaction field and lane field and segment the time period to generate toll operation records; Step 2: Divide the toll collection operation records into ETC vehicle records and MTC vehicle records according to the transaction medium, and generate classified statistical records by counting the traffic volume; Step 3: Calculate the ETC arrival rate and MTC arrival rate from the classification statistics records, and extract the unit throughput from the toll operation records and generate the ETC service rate and MTC service rate after anomaly removal and scale conversion; Step 4: Couple arrival rate and service rate, introduce the variable of number of open lanes, construct a dual parallel multi-server queuing evaluation model, calculate service intensity and queuing time to generate queuing evaluation records; Step 5: Project the arrival rate using service capacity as a scale to form ETC occupancy intensity and MTC occupancy intensity, and generate demand configuration records by calibrating the total scale and bias direction; Step 6: Generate a candidate configuration set based on the total number of lanes and service intensity, and select the efficiency combination with the minimum queuing time by combining queuing evaluation records and demand configuration records; Step 7: Filter the qualified configuration records from the candidate configuration set whose queuing time meets the service threshold, and determine the cost-saving combination according to the principle of the minimum number of lanes opened; Step 8: Output the saving combination if a saving combination exists, and output the efficiency combination if no saving combination exists, forming the opening and closing results containing the number of ETC openings, the number of MTC openings, and the number of closings.

2. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes as described in claim 1, characterized in that, Step one specifically involves: Extract transaction fields, lane fields, time period fields, and threshold fields from the toll station operation data. Standardize the transaction time format and organize the transaction medium code for the transaction fields. Verify the lane identification and label the lane type for the lane fields to generate a field-organized record. Based on the lane identifier verification results in the field regularization record, the number of available lanes is counted to generate the total number of lanes. Based on the threshold field in the field regularization record, the upper limit of average queuing time is extracted to generate the service threshold. Based on the time period field in the field-organized record, establish the analysis time period boundary, and map the transaction field after the transaction time format is unified to the analysis time period boundary to form a time period segmentation record; The time period segmentation records, lane type identification results, total number of lanes, and service thresholds are linked and organized according to the toll station identification to generate toll operation records.

3. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step two specifically involves: Extract the transaction medium code, transaction time, lane identification, toll station identification and time period identification from the toll operation record. Establish a vehicle type determination table according to the transaction medium code, and map the antenna transaction code to the ETC type and the CPC card transaction code and the hand-torn ticket transaction code to the MTC type. Based on the vehicle type determination table, the toll operation records are matched by type. The toll operation records that match the ETC type are classified into the ETC vehicle record, and the toll operation records that match the MTC type are classified into the MTC vehicle record. ETC vehicle records are grouped and statistically analyzed according to toll station identification and time period identification to generate ETC traffic volume; MTC vehicle records are grouped and statistically analyzed according to toll station identification and time period identification to generate MTC traffic volume. ETC vehicle records, MTC vehicle records, ETC traffic volume, and MTC traffic volume are linked and organized according to toll station identifiers and time period identifiers to generate classified statistical records for use in calculating ETC arrival rate and MTC arrival rate.

4. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes as described in claim 1, characterized in that, Step three specifically involves: Extract ETC traffic volume, MTC traffic volume, and time period identifier from the classified statistical records. Determine the time period duration from the time period identifier. Calculate the ETC arrival rate by comparing the ETC traffic volume with the time period duration. Calculate the MTC arrival rate by comparing the MTC traffic volume with the time period duration. Extract lane identification, lane type calibration results, and transaction time from the toll operation records. Based on the lane identification and lane type calibration results, aggregate the number of vehicles passing through within the same transaction time period to generate ETC unit throughput and MTC unit throughput. Based on the historical statistical range corresponding to the lane type calibration results, deviation judgment is made on the ETC unit throughput and MTC unit throughput, abnormal unit throughput exceeding the historical statistical range is removed, and the retained unit throughput is converted to a time scale. The ETC unit throughput after time scale conversion is determined as the ETC service rate, and the MTC unit throughput after time scale conversion is determined as the MTC service rate. The ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate are then linked and organized according to the toll station identifier and time period identifier.

5. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step four specifically involves: Arrival service parameters are extracted from ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate. The number of ETC lanes opened is used as the service station capacity of the ETC queuing evaluation branch, and the number of MTC lanes opened is used as the service station capacity of the MTC queuing evaluation branch. A dual-parallel multi-service station queuing evaluation model is constructed. In the ETC queuing evaluation branch, the ETC arrival rate, ETC service rate, and number of ETC-enabled lanes are used for capacity matching calculation to generate ETC service intensity. In the MTC queuing evaluation branch, the MTC arrival rate, MTC service rate, and number of MTC-enabled lanes are used for capacity matching calculation to generate MTC service intensity. The ETC waiting probability is calculated based on the ETC service intensity and the number of ETC lanes in operation, and the ETC queuing time is converted from the ETC waiting probability. Similarly, the MTC waiting probability is calculated based on the MTC service intensity and the number of MTC lanes in operation, and the MTC queuing time is converted from the MTC waiting probability. Arrival rate weights are formed based on ETC arrival rate and MTC arrival rate. The arrival rate weights are then used to weight and aggregate the ETC queuing time and MTC queuing time to generate a comprehensive queuing time. ETC service intensity, MTC service intensity, ETC queuing time, MTC queuing time and comprehensive queuing time are then linked and organized according to toll station identifiers and time period identifiers to generate a queuing evaluation record.

6. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step five specifically involves: The arrival service parameters under the same toll station identifier and the same time period identifier are extracted from ETC arrival rate, MTC arrival rate, ETC service rate and MTC service rate. The ETC service rate is determined as the single lane service capacity of ETC vehicles, and the MTC service rate is determined as the single lane service capacity of MTC vehicles. The ETC arrival rate is converted into capacity occupancy based on the ETC service rate to generate ETC occupancy intensity. The MTC arrival rate is converted into capacity occupancy based on the MTC service rate to generate MTC occupancy intensity. The total quantity of lane resources is generated by summing the ETC occupancy intensity and MTC occupancy intensity. The difference between the ETC occupancy intensity and MTC occupancy intensity is calculated to generate the bias direction that represents the lane resource bias type. The ETC occupancy intensity, MTC occupancy intensity, total volume scale, and bias direction are associated and organized according to the toll station identifier and time period identifier to generate a demand configuration record for screening candidate configuration sets.

7. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step six specifically involves: Establish a quantity balance relationship between the number of ETC activated, MTC activated, and deactivated lanes based on the total number of lanes, and form an initial configuration record according to non-negative integer values; The number of ETC activations and MTC activations in the initial configuration record are introduced into the dual-parallel multi-server queuing evaluation model to calculate the ETC service strength, MTC service strength and comprehensive queuing time. The initial configuration record in which both ETC service strength and MTC service strength meet the stability condition is retained to generate a candidate configuration set. Extract ETC occupancy intensity, MTC occupancy intensity, total scale, and bias direction from the demand configuration record. Perform demand adaptation calculation on the number of ETC and MTC enabled in the candidate configuration set to generate configuration adaptation results. By combining the overall queuing time and configuration adaptation results in the queuing evaluation records, the candidate configuration set is sorted and filtered, and the candidate configuration with the minimum overall queuing time and configuration adaptation results that meet the bias direction is determined as the efficiency combination.

8. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step seven specifically involves: Extract candidate configuration records from the candidate configuration set, match the candidate configuration records with the comprehensive queuing time in the queuing evaluation records, compare the comprehensive queuing time with the service threshold, and generate the threshold comparison result. Candidate configuration records whose threshold comparison results do not exceed the service threshold are identified as compliant configuration records, and candidate configuration records whose threshold comparison results exceed the service threshold are removed from the candidate configuration set. The number of ETC and MTC activated in the compliance configuration records is summed to generate the total number of activated lanes, and the compliance configuration records are arranged in ascending order of the total number of activated lanes. In the qualified configuration record with the minimum total number of open lanes, the saving combination is determined according to the comprehensive queuing time from small to large, and the saving combination is correlated with the number of ETC open, MTC open and closed.

9. The method for optimizing lane opening and closing at highway toll stations based on ETC and MTC hybrid lanes according to claim 1, characterized in that, Step eight specifically involves: The integrity of the savings combination is determined. A savings combination existence mark is generated when the savings combination is associated with the number of ETC activations, MTC activations, and deactivations. A savings combination missing mark is generated when the savings combination is not associated with the number of ETC activations, MTC activations, and deactivations. When a saving combination is marked, the saving combination is identified as the target open / closed combination; when a saving combination is missing a mark, the efficiency combination is identified as the target open / closed combination. Extract the number of ETC activated, MTC activated, and deactivated from the target activation / deactivation combination, and verify the consistency of the number of ETC activated, MTC activated, and deactivated with the total number of lanes; After the quantity consistency verification is passed, the target opening and closing combination, toll station identifier, time period identifier, and comprehensive queuing time are linked and organized to form the opening and closing result including the number of ETC openings, the number of MTC openings, and the number of closings.

Images