CN109949098B - Method for calculating number of lanes of highway toll station - Google Patents
Method for calculating number of lanes of highway toll station Download PDFInfo
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Abstract
The invention relates to a method for calculating the number of lanes of a highway toll station, which comprises the following steps: the method comprises the steps of carrying out statistical analysis on service time of each type of vehicle in a toll station in different toll ways, and establishing a service time calculation model in a multi-charging way according to service time analysis; establishing a toll station vehicle passing and service simulation model based on a VISSIM platform, and acquiring the actual lane number requirement of the toll station; calculating and correcting the traffic volume in the design hour by using a queuing theory according to the number of lanes and service time required by the toll station; carrying out regression fitting on the corrected design hour traffic volume and the actual design hour traffic volume to obtain a traffic volume conversion model; and selecting a typical toll station to calculate and verify the number of lanes. The lane number calculation method for the toll station provided by the invention provides support for designing the lane number of the toll station for newly building and modifying the toll station by a traffic department.
Description
Technical Field
The invention relates to the field of toll station design, in particular to a method for calculating the number of lanes of a highway toll station.
Background
In recent years, with the rapid development of traffic industry, the quantity of retained automobiles is continuously increased, congestion of toll stations on highways often occurs, and due to the fact that the number of lanes of a toll station is too large, lanes of a part of toll stations are idle and resources are wasted, and therefore, the reasonable design of the number of lanes of the toll station is particularly important.
The method for calculating the number of the lanes comprises an empirical method, a lane traffic capacity calculation method, a method based on a queuing theory and the like, wherein the method for calculating the number of the lanes by using the queuing theory is the most suitable method, a lane number calculation table is drawn by using the theory, and the number of the lanes is selected from the table according to the comprehensive service time and the designed hour traffic volume of the lanes of the toll station. In China, the reference for calculating the number of lanes is based on the technical requirement on toll road networking (published in 2007), a lane number calculation table is provided in the requirement, but the method for determining the service time and the traffic volume cannot meet the actual requirement, and the method mainly comprises the following steps: in the requirements, only experience values of service time of outlet artificial cash and inlet artificial card issuing are provided, but the service time distribution of each mode is different aiming at the current multi-charging modes such as WeChat, Payment treasure payment and card swiping payment, so that the service time is not suitable to be selected according to the experience values; in addition, although a formula for converting the traffic volume of the truck according to a fixed proportion is provided in the requirement, the conversion result is usually inaccurate according to actual measurement. Therefore, the conventional lane number calculation method cannot meet the actual requirement.
Therefore, in order to ensure the passing efficiency of the toll station vehicles, the number of lanes of the toll station needs to be reasonably designed, and the problems of traffic jam, resource waste and the like caused by unreasonable lane number setting are solved, so that a new calculation method is urgently needed.
Disclosure of Invention
The invention aims to provide a method for calculating the number of lanes of a highway toll station, which can realize accurate calculation of the number of lanes of the toll station and solve the problems of traffic jam, resource waste and the like caused by unreasonable design of the number of lanes.
The invention provides a method for calculating the number of lanes of a highway toll station, which comprises the following steps:
the method comprises the following steps of carrying out statistical analysis on a multi-element charging mode and service time distribution of the multi-element charging mode of the highway toll station, and establishing a service time calculation model of the multi-element charging mode according to the statistical analysis;
the method comprises the steps of establishing a toll station vehicle passing and service simulation model by using VISSIM software, taking actual traffic volume data, service time data, vehicle types, user use ratio data and the like of the toll station as model input, and determining the number of lanes required by the toll station according to the average queuing length of the lanes output by the model;
establishing a corrected traffic volume calculation model based on a queuing theory, determining model input parameters, and calculating corrected traffic volume of a toll station;
performing regression fitting on the corrected traffic volume and the actual traffic volume by adopting polynomial regression to obtain a traffic volume conversion model;
and calculating the number of the toll station lanes by combining a lane number calculation table according to the service time calculation model and the traffic conversion model.
Further, the analyzing diversified charging modes for highway charging includes:
the toll station exit comprises the service time of cash charging, mobile charging (WeChat and Paibao payment) and card swiping charging (ETC card-held truck driving artificial toll lane of the highway toll station); the toll gate entrance comprises service time for manual card issuing and card swiping for entering the toll gate (a truck with an ETC card at a highway toll gate runs on a manual toll lane to enter the toll gate).
Further, the establishing of the service time calculation model of the multi-charging mode includes:
the service time refers to the time that the vehicle enters the toll station to start card collection or payment until the card collection or payment is completed, the service time of each different card collection and payment mode has distribution difference, and a service time calculation model of a multi-element charging mode is established and comprises an outlet and an inlet.
Further, the service time calculation model, for an exit direction, includes:
wherein: t is tckService time for toll station exit; n is the number of vehicle types; lxjThe proportion of users is charged by cash; lydAdopting the mobile charging user ratio; lskAdopting the proportion of the user who charges by swiping the card; t is txji(i 1, 2.. n) service hours charged with cash for the ith vehicle type; p is a radical ofxji(i 1, 2.. n.) is the proportion of the ith vehicle type charged by cash; t is tydi(i 1, 2.., n) service hours charged for the movement of the ith vehicle type; p is a radical ofydi( i 1, 2.. n.) is the proportion of the ith vehicle type with mobile charging; t is tski( i 1, 2.., n) service time charged by swiping a card for the ith vehicle type; p is a radical ofski(i ═ 1, 2.., n) is the proportion of the ith vehicle type charged by card swiping.
Further, the service time calculation model, for the entry direction, includes:
wherein: t is trkService time for toll station entrance; n is the number of vehicle types; lzdIs the automatic card issuing user proportion; lrgThe ratio of manual card issuing users is adopted; lskThe ratio of the users who enter the station by swiping the card is; t is tzdi(i 1, 2.., n) is the service time of the automatic card issuing adopted by the model i; p is a radical ofzdi( i 1, 2.. n.) is the proportion of the ith vehicle type by automatic card issuing;trgi( i 1, 2.., n) is the service time of manual card issuing for the ith vehicle type; p is a radical ofrgi( i 1, 2.. n.) is the proportion of the ith vehicle type by manually issuing a card; t is tski( i 1, 2.., n) is the service time of the ith vehicle type entering the station by swiping a card; p is a radical ofskiAnd (i ═ 1, 2., n) is the proportion of the vehicle type i which is swiped to the station.
Further, the toll station vehicle passing and service simulation model comprises:
the method comprises the steps of utilizing VISSIM software to simulate and model a toll station based on actual data, designing a toll station simulation base map by utilizing CAD software, designing and arranging a road network on the base map, designing a vehicle generation module, designing a vehicle driving module, designing a toll service module, designing a path decision module and setting simulation parameters.
The simulation model can simulate the traffic flow of different vehicle types with different vehicle flow rates, drive in and drive out of the toll station with certain speed distribution, simulate the process of parking charging and card getting of different vehicle types with different charging modes at the toll station, and realize the function of accelerating the driving away after the vehicles stop for a period of time at the toll station. The simulation model can simulate the whole process of vehicle passing and service of the toll station.
Further, the inputting the actual data of the toll station as a model comprises:
actual traffic volume data, service time data, vehicle type and user use ratio data of the toll station;
the actual traffic data of the toll station comprises: annual traffic volume and peak hour traffic volume of toll stations;
the service time data includes: service time of different vehicle types with different card receiving and payment modes is adopted at the entrance and exit of the toll station;
vehicle model and user usage ratio data: the vehicle type proportion of different vehicle types and the use proportion of each charging mode.
Further, the model outputs parameters to determine the actual lane number requirement of the toll station, and the method comprises the following steps:
the output parameters adopt simulation model output parameters, including: the average queuing length L (m) of the lanes determines the actual lane number requirement according to the following formula:
l is the simulation output queue length (m), j is the simulation number of times, W is the set threshold, and W is 6 m. The number of lanes corresponding to the above equation is set as the actual required number of lanes.
Further, the establishing of the corrected traffic volume calculation model based on the queuing theory and the determining of the model input parameters to calculate the corrected traffic volume includes:
the queuing theory is a mathematical theory and a method for researching a system random service process, can describe a vehicle service process of a highway toll station, and establishes a calculation model for correcting traffic volume according to a single-way queuing multi-channel model of the queuing theory, wherein: the system service strength rho is lambda/mu; traffic intensity gamma is rho/sxz(ii) a The average waiting vehicle number q in the queue is n-rho (vehicles); waiting vehicles per lane m-q/sxz(vehicle); the average time d of the vehicle in the system is q/lambda + 1/mu (second); the average time w of the vehicles in the queue is q/lambda (seconds);
probability of no vehicle in the system:
average waiting number of vehicles in system
Further, determining model input parameters, comprising:
and calculating the comprehensive service time of the toll stations according to the service time calculation model, and combining the actual required lane number of each toll station to form calculation model input for correcting the traffic volume.
Further, calculating the corrected design hour traffic volume comprises:
based on the model input parameters and the equations described above,the corrected design hour traffic volume may be calculated. Including both directions of access, i.e. DHVXZ＝{DHVXZ-ck,DHVXZ-rk}。
Wherein the exit direction corrects the hourly traffic volume, and the formula is as follows:
the entrance direction corrects the hourly traffic volume, and the formula is as follows:
wherein, DHVXZ-ckFor modified hourly traffic in the egress direction, DHVXZ-rkThe corrected hourly traffic volume is the entry direction.
Further, performing regression fitting on the corrected traffic volume and the actual traffic volume to obtain a traffic volume conversion model, including:
and (3) establishing a regression model by combining the actual design hour traffic volume and the corrected design hour traffic volume with the medium-large vehicle proportion, wherein the expression is as follows:
DHVXZ＝DHV×f(u)
further, the establishing of the traffic conversion model by adopting polynomial regression includes:
a quadratic polynomial regression is adopted to construct a model, and the expression is as follows:
DHVXZ＝DHV×(4.58u2-5.69u+3.06)
there is a strong correlation (R) between independent variables and dependent variables in the model20.8934), wherein sig 5.4896E-12<0.05, the model passed the significance test.
Further, the calculating the number of the toll station lanes by combining a lane number calculation table according to the service time calculation model and the traffic conversion model comprises:
and calculating the comprehensive service time of the toll station according to the entrance and exit service time calculation model, and then converting the designed hour traffic of the toll station according to a traffic conversion formula to obtain the corrected designed hour traffic. And then the required number of lanes is searched and obtained by combining a lane number calculation table of 'toll road networking technical requirements'.
The beneficial effect who adopts above-mentioned scheme is:
the service time calculation model and the traffic conversion model provided by the invention can effectively solve the problem of inaccurate calculation of service time and traffic, can realize the optimized calculation of the number of the toll stations by combining the lane number calculation table, provide decision basis for decision management of a road management department, improve the overall passing efficiency of the toll stations and further improve the road service quality.
Compared with the existing method, the calculation model provided by the invention has the characteristics of accurate calculation, simple parameters and easiness in acquisition, can provide a basis for selecting the number of newly built and expanded lanes of the toll station, and improves the operation efficiency of the whole toll station.
Drawings
Fig. 1 is a flowchart of a method for calculating the number of lanes at a toll station of a highway according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a distribution of service time in a multi-charging mode according to an embodiment of the present invention;
FIG. 3 is a schematic view of a simulation model;
FIG. 4 is a schematic diagram of simulation model reliability verification;
fig. 5 is a flowchart of a lane number calculation method in the present embodiment.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In each embodiment of the invention, compared with the existing method, the calculation model provided by the invention has the characteristics of accurate calculation, simple parameters and easy acquisition, can provide a basis for selecting the number of newly built and newly expanded lanes of the toll station, and improves the operation efficiency of the whole toll station.
As shown in fig. 1, the flowchart of the method for calculating the number of lanes at the highway toll station provided in this embodiment specifically includes:
and 11, carrying out statistical analysis on the multivariate charging mode and the service time distribution of the expressway toll station, and establishing a service time calculation model of the multivariate charging mode according to the statistical analysis.
In this embodiment, the statistical analysis of service time distribution for a plurality of charging modes of a typical toll station in shanxi province mainly includes:
the toll station exit comprises service time distribution of cash charging, mobile charging (WeChat, Paibao payment) and card swiping charging (ETC card-held truck driving artificial toll lane of the highway toll station); the toll gate entrance includes service time distribution using manual card issuing and card swiping into the toll gate (a truck with an ETC card at a highway toll gate travels on an artificial toll lane into the toll gate).
FIG. 2 shows the distribution of the service time of the small cars in the exit multi-charging mode at the toll station of the highway obtained by investigation and statistics, and the mean value of the service time of the small cars paid by cash is 16s after analysis; the average value of the service time of the mobile payment mini car is 21 s; the mean value of ETC card swiping payment mini car service time is 13s, the service time of mobile payment is higher than cash payment and card swiping payment, the card swiping payment service time is the minimum, and the distribution of the vehicle service time of different charging modes has difference.
Through analysis, service times of different toll collection modes and vehicle types are different, so that a toll station comprehensive service time calculation model capable of fusing multiple payment modes and vehicle types together needs to be provided to design the number of toll station lanes.
The service time calculation model of the multi-charging mode comprises a toll station exit service time calculation model and a toll station entrance service time calculation model.
In this embodiment, the export service time calculation model formula is as follows:
wherein: t is tckService time for toll station exit; n is the number of vehicle types; lxjThe proportion of users is charged by cash; lydAdopting the mobile charging user ratio; lskAdopting the proportion of the user who charges by swiping the card; t is txji( i 1, 2.. n) service hours charged with cash for the ith vehicle type; p is a radical ofxji( i 1, 2.. n.) is the proportion of the ith vehicle type charged by cash; t is tydi( i 1, 2.., n) service hours charged for the movement of the ith vehicle type; p is a radical ofydi( i 1, 2.. n.) is the proportion of the ith vehicle type with mobile charging; t is tski( i 1, 2.., n) service time charged by swiping a card for the ith vehicle type; p is a radical ofski(i ═ 1, 2.., n) is the proportion of the ith vehicle type charged by card swiping.
In this embodiment, the entry service time calculation model formula is as follows:
wherein: t is trkService time for toll station entrance; n is the number of vehicle types; lzdIs the automatic card issuing user proportion; lrgThe ratio of manual card issuing users is adopted; lskThe ratio of the users who enter the station by swiping the card is; t is tzdi( i 1, 2.., n) is the service time of the automatic card issuing adopted by the model i; p is a radical ofzdi( i 1, 2.. n.) is the proportion of the ith vehicle type by automatic card issuing; t is trgi( i 1, 2.., n) is the service time of manual card issuing for the ith vehicle type; p is a radical ofrgi( i 1, 2.. n.) is the proportion of the ith vehicle type by manually issuing a card; t is tski( i 1, 2.., n) is the service time of the ith vehicle type entering the station by swiping a card; p is a radical ofskiAnd (i ═ 1, 2., n) is the proportion of the vehicle type i which is swiped to the station.
And step 12, inputting the actual data of the toll station as a model, establishing a toll station vehicle passing and service simulation model, and determining the actual lane number requirement of the toll station according to the output parameters of the model.
The actual data of the toll station as model input mainly comprises the following steps: the actual hourly traffic volume of 15 sample toll stations in Shanxi province, the service time, the vehicle type proportion and the toll mode proportion of different vehicle types in each toll mode are selected as input parameters of a simulation model, and a basis is provided for constructing a traffic volume conversion model.
The establishment of the toll station vehicle passing and service simulation model comprises the following steps: a toll station vehicle passing and service simulation model is established based on a VISSIM platform, and firstly, a toll station simulation base map is designed by utilizing CAD software, a road network is designed and arranged on a map, a vehicle generation module is designed, a vehicle traveling module is designed, a toll service module is designed, a path decision module is designed, and simulation parameters are set.
Fig. 3 is a schematic view of a simulation model, which can simulate the traffic flow of each vehicle type with different vehicle flow rates, drive in and out of the toll station with certain speed distribution, and simulate the process of parking charging and getting-in of each vehicle type with different charging modes at the toll station, and the vehicle can realize the function of accelerating the drive-out after stopping for a period of time at the toll station, and can simulate the whole process of traffic vehicle passing and service at the toll station.
Fig. 4 is a schematic diagram of simulation model reliability verification, in order to verify the correctness of the simulation model, absolute errors are calculated for actual hourly traffic volume and simulated output hourly traffic volume of each toll station, and through simulation modeling of 30 model samples of 15 toll station separation inlets, the absolute errors are all within 8%, and the simulation model meets the precision requirement.
The model output parameters are: average queuing length l (m) of the lanes.
The actual lane number requirement of the toll station is determined as follows: and determining the lane number requirement by setting a queuing length threshold. The method comprises the following steps:
according to the output parameters (average queuing length L: m) of the established vehicle passing and service simulation model of each toll station, the number of lanes meeting the design requirements can be determined. Referring to 'road engineering technical standard', the length of a medium-sized and small-sized vehicle is 6m, a set threshold W is 6m, L is required to be smaller than the set threshold to guarantee design requirements, and the maximum value of L obtained by j times of simulation is required. Specifically, the discrimination is performed according to the following formula:
l is the simulation output queue length (m), j is the simulation number of times, W is the set threshold, and W is 6 m. Simulating the model, and if L satisfies the above formula, setting the input s as the number of lanes s satisfying the design requirementxz(ii) a If L does not meet the rule (3), resetting s and simulating again until the requirement is met, wherein the number of lanes meeting the condition is s meeting the design requirementxzThe toll station can not be jammed or the lane is idle. From this the actual lane number requirements of the toll booth can be determined.
And step 13, establishing a corrected traffic volume calculation model based on a queuing theory, determining model input parameters, and calculating corrected traffic volume of the toll station.
The process of establishing a corrected traffic volume calculation model based on a queuing theory, wherein vehicles arrive at the entrance or the exit of the expressway toll station at random, and pass through the toll station after queuing can be described by a queuing system model in mathematical statistics. In this embodiment, the conversion model is as follows:
ρ ═ λ/μ equation (4)
γ＝ρ/sxzFormula (5)
q-n- ρ equation (8)
m＝q/sxzFormula (9)
Q/λ +1/μ equation (10)
w is q/lambda formula (11)
Wherein P (0) is the probability of no vehicle in the system; n is the average number of waiting vehicles (vehicles) in the system; q is the average waiting vehicle number (vehicles) in the queue; m is the number of waiting vehicles (vehicles) per lane; d is the average elapsed time (seconds) of the vehicle in the system; w is the average elapsed time (seconds) of the vehicle in the queue; lambda is the average arrival rate of the vehicle; μ is the system average service rate (vehicle/hour); rho is service intensity; gamma is traffic intensity; sXZNumber of lanes
The determined model parameters are: the comprehensive service time of the toll stations calculated by the service time calculation model is combined with the number of lanes actually required by each toll station to form calculation model input for correcting traffic volume. In this embodiment, the calculation of the toll station repair orthogonal flux is performed according to the following formula based on the model input parameter:
DHVXZ＝{DHVXZ-ck,DHVXZ-rkequation (14)
Wherein, DHVXZ-ckFor modified hourly traffic in the egress direction, DHVXZ-rkThe corrected hourly traffic volume is the entry direction.
And step 14, performing regression fitting on the corrected traffic volume and the actual traffic volume by adopting polynomial regression to obtain a traffic volume conversion model.
The regression fitting of the corrected traffic volume and the actual traffic volume by adopting polynomial regression is as follows: according to the calculated DHV of each toll station entranceXZAnd constructing a DHV conversion model by combining the actual design hour traffic volume DHV and the medium and large vehicle proportion u:
DHVXZDHV × f (u) formula (15)
The method for constructing the traffic conversion model by adopting quadratic polynomial regression comprises the following steps:
DHVXZ＝DHV×(4.58u2-5.69u +3.06) formula (16)
After the model is established, the annual average daily traffic volume AADT of the toll station is converted into DHV according to the formula (18) and then converted into DHV according to the formula (17)XZAnd combining the calculated service time, and looking up a table to calculate the number of required lanes.
And step 15, calculating the number of the toll station lanes by combining a lane number calculation table according to the service time calculation model and the traffic conversion model.
Fig. 5 is a flow of calculating the number of lanes in the present embodiment, and first, the comprehensive service time of the toll station is calculated according to the entrance/exit service time calculation model; then, converting the traffic volume of the toll station in the design hour according to a formula (16) to obtain the traffic volume of the corrected design hour; and (4) searching the required number of lanes by combining a lane number calculation table of 'toll road networking technical requirements'.
The service time calculation model and the design hour traffic conversion model provided by the invention can effectively solve the problem of inaccurate calculation of service time and traffic, can realize the optimized calculation of the number of the toll stations by combining the lane number calculation table, provides decision basis for decision management of a road management department, improves the overall passing efficiency of the toll stations, and further improves the road service quality.
Compared with the existing method, the calculation model provided by the invention has the characteristics of accurate calculation, simple parameters and easiness in acquisition, can provide a basis for selecting the number of newly built and expanded lanes of the toll station, and improves the operation efficiency of the whole toll station.
Indeed, the effectiveness of the present embodiment may be further illustrated by example validation. It should be noted that the parameters applied in the verification do not affect the generality of the present invention.
Verifying content
The data source used for verification in the embodiment is traffic volume data, service time data and vehicle type payment mode proportion data of 2017 years at an export of an elm toll station in Shanxi province.
Firstly, the comprehensive service time of the toll station is calculated according to a service time calculation model. According to the statistical analysis of the service time data, the proportion of each charging mode, the proportion of the vehicle type and the service time of the charging station can be obtained, and the specific numerical values are as follows:
according to the calculation formula of the export service time, the service time can be calculated to obtain tck23.86s, take 24 s.
And then calculating and correcting the traffic volume at the design hour by using a traffic volume conversion model according to actual data, wherein the method comprises the following steps: firstly, the actual annual average daily traffic volume AADT of the toll station is converted into the design hour traffic volume, and the calculation is carried out according to a formula (17), wherein: k is the traffic coefficient in the design hour (the standard value is 0.12); d is a direction unbalance coefficient (the standard value is 0.6), and K, D is selected according to the standard value.
DHV ═ AADT × K × D formula (17)
The average daily traffic AADT in the actual year is 6959(pcu/d), and DHV is 501 (pcu/h). The medium-large duty ratio u is 53% obtained from actual traffic volume data, and the design hour traffic volume DHV is calculated and corrected according to a traffic volume conversion modelXZ667 (pcu/h). According to the calculated service time 24s, 6 lanes are obtained from the lane number calculation table, 1 lane is added in consideration of ETC charging, and 7 exit lanes are totalized.
In order to verify the lane number calculation table result, a vehicle passing and simulation model of the elm toll station is established, and simulation is carried out. The simulation output result can be obtained:
| lane numbering | MTC-1 | MTC-2 | MTC-3 | MTC-4 | MTC-5 | MTC-6 | ETC |
| Average queue length (m) | 4 | 5 | 6 | 7 | 7 | 6 | 0 |
The simulation output result can calculate the average queuing length L of the MTC lane to be 5.83m, and the ETC lane has no vehicle queuing, thereby meeting the design requirement of 'toll road networking technical requirement' on the number of lanes of a toll station. If the DHV is 705(pcu/h), which is obtained by converting the traffic volume according to the original method, according to the service time 14-20s according to the original calculation method, at most 5 lanes can be selected according to the maximum service time 20s, and if 4 lanes can be selected according to the service time 14s, the method can realize the optimized calculation of the number of lanes, and solve the problems of traffic jam and lane idle at the toll station.
In summary, the service time calculation model and the designed hourly traffic volume conversion model provided by the invention can effectively solve the problem of inaccurate calculation of service time and traffic volume, can realize the optimized calculation of the number of lanes of the toll station by combining the lane number calculation table, provides decision basis for decision management of a road management department, improves the overall passing efficiency of the toll station, and further improves the road service quality. Compared with the existing method, the provided calculation model has the characteristics of accurate calculation, simple parameters and easiness in obtaining, can provide a basis for selecting the number of newly built and expanded lanes of the toll station, and improves the operation efficiency of the whole toll station.
Finally, the above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention, which should be covered by the claims of the present invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. A method for calculating the number of lanes of a highway toll station is characterized by comprising the following steps:
the method comprises the following steps of carrying out statistical analysis on a multi-element toll collection mode of the highway toll station and service time distribution of the multi-element toll collection mode, and establishing a toll station entrance and exit service time calculation model of the multi-element toll collection mode according to the statistical analysis;
establishing a toll station vehicle passing and service simulation model, taking actual traffic volume data, service time data, vehicle type and user use ratio data of the toll station as model input, and determining the number of lanes actually required by the toll station according to the average queuing length of the lanes output by the model;
establishing a corrected traffic volume calculation model based on a single-way queuing multi-channel model of a queuing theory, determining model input parameters, and calculating corrected traffic volume of a toll station;
performing regression fitting on the corrected traffic volume and the actual traffic volume by adopting polynomial regression to obtain a traffic volume conversion model;
and calculating the number of the toll station lanes by combining a lane number calculation table according to the service time calculation model and the traffic conversion model.
2. The method as claimed in claim 1, wherein the multiple charging method and the service time thereof comprise:
the service time refers to the time that the vehicle enters the toll station to start getting the card or paying the fee until the card getting or paying the fee is completed, the service time of each different card getting and paying mode has distribution difference, wherein the service time of the toll station outlet comprises the service time of cash charging, mobile charging and card swiping charging; the entrance of the toll station comprises service time for manually issuing cards and swiping cards to enter the station; the mobile charging includes: paying by WeChat and Paibao; the card-swiping charging comprises the following steps: the highway toll station holds a truck of the ETC card to run an artificial toll lane; the card swiping enters the station and comprises: the truck with the ETC card at the highway toll station runs on an artificial toll lane to enter the toll station.
3. The method for calculating the number of lanes of the highway toll station according to claim 1, wherein the step of establishing a toll station entrance and exit service time calculation model in a multi-charging mode comprises the following steps:
an egress service time calculation model and an ingress service time calculation model.
4. The method for calculating the number of lanes at the highway toll station according to claim 1, wherein the step of establishing a toll station vehicle passing and service simulation model comprises the following steps:
drawing a simulation base map, designing a road network, designing a vehicle generation module, designing a vehicle running module, designing a charging service module, designing a path decision module and setting simulation parameters.
5. The method of claim 1, wherein the step of inputting the actual traffic data, service time data, vehicle type and user usage ratio data of the toll station as a model comprises:
the actual traffic data of the toll station comprises: annual traffic volume and peak hour traffic volume of toll stations;
the service time data includes: service time of different vehicle types with different card receiving and payment modes is adopted at the entrance and exit of the toll station;
vehicle model and user usage ratio data: the vehicle type proportion of different vehicle types and the use proportion of each charging mode.
6. The method for calculating the number of lanes at the highway toll station according to the claim 1, wherein the average queuing length of the lanes output according to the model comprises the following steps:
average queuing length L of vehicles of each toll lane, unit: and (m) rice.
7. The method for calculating the number of lanes of the highway toll station according to claim 6, wherein the step of determining the number of lanes actually required by the toll station comprises the following steps:
determining the number of lanes meeting the design requirement of the toll station according to the model output parameters and the following formula;
l is the simulation output queue length (m), j is the simulation times, W is the set threshold: w is 6m, and the number of lanes corresponding to the above expression is set as the actual required number of lanes.
8. The method of claim 1, wherein the step of performing regression fitting on the corrected traffic volume and the actual traffic volume comprises:
and establishing a regression model, namely a traffic conversion model, by using a quadratic polynomial in combination with the actual design hour traffic and the corrected design hour traffic and the medium and large vehicle proportion.
Priority Applications (1)
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| CN110503827A (en) * | 2019-08-12 | 2019-11-26 | 兰州交通大学 | A kind of container Intelligent gateway energy-saving control device |
| CN112446972B (en) * | 2020-10-13 | 2021-11-19 | 华南理工大学 | System and method for inducing vehicles to orderly enter toll station |
| CN113850991B (en) * | 2021-08-31 | 2022-11-01 | 北京北大千方科技有限公司 | Traffic condition identification method and device for toll station, storage medium and terminal |
| CN114005274B (en) * | 2021-10-21 | 2023-03-03 | 浙江综合交通大数据开发有限公司 | Expressway toll station graded linkage management and control method based on equivalent weight of passenger car |
| CN115083158B (en) * | 2022-06-14 | 2023-06-27 | 四川交通职业技术学院 | Method for measuring and calculating number of mixed lanes of highway toll station |
| CN115083155B (en) * | 2022-06-14 | 2023-06-27 | 四川交通职业技术学院 | Method for measuring and calculating number of ETC lanes on highway toll station |
| CN115359659B (en) * | 2022-08-19 | 2023-06-20 | 山西省交通新技术发展有限公司 | Lane opening and closing configuration method and system |
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