CN105930914A - City bus optimal charging structure charge determination method based on origin-destination distance - Google Patents

City bus optimal charging structure charge determination method based on origin-destination distance Download PDF

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CN105930914A
CN105930914A CN201610201777.3A CN201610201777A CN105930914A CN 105930914 A CN105930914 A CN 105930914A CN 201610201777 A CN201610201777 A CN 201610201777A CN 105930914 A CN105930914 A CN 105930914A
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刘志远
黄迪
庄焱
曲小波
程启秀
胡冕
胡一冕
刘子涵
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Southeast University
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Abstract

The invention discloses a city bus optimal charging structure charge determination method based on origin-destination distance, and presents a series of corresponding estimation models and optimal charging structure calculation algorithms, and the method comprises the steps: (1) detailed summary and analysis are performed on city bus ticket system mode in prior art, advantages, disadvantages and application range of a ticket price structure are pointed out, on this basis, the ticket price structure of origin-destination Euclidean distance based on the distance is provided and analyzed; (2) in an evaluation model, a game playing process between government, enterprises and passengers is described through a game theory, and a Logit passenger flow distribution model comprising enterprise maximum return as upper model and elastic demand as lower model is constructed; (3) a genetic algorithm is adopted to solve the model, and verification analysis is performed on the model and the algorithm through a small-size bus network.

Description

The charge of city bus optimum charging structure based on origin and destination distance determines method
Technical field
The present invention relates to a kind of new method determining ticket price structure and tariff level according to bus trip passenger origin and destination air line distance, belong to urban traffic control and control field.
Background technology
Under the guidance of the national strategy such as " public traffic in priority " and " greatly developing public transport ", under existing road network and transit network, how to utilize urban public transport best price strategy to improve traffic resource allocative efficiency, it has also become the hot issue that city bus operating practice and public transport planning are studied with management theory.Urban public transport ticket system and fare level are the important component parts of urban public tranlport system, which determine the share rate of urban public transport, are one of direct factors affecting the choice for traveling of people and the public transportation system equilibrium of supply and demand.Public transport fares structure and level unreasonable by causing the unbalance of Transit assignment and Public Resource configuration, affects the sustainable development of public transit system.The advantage such as have that charge method is simple due to traditional flat fare and extras cost is relatively low and be widely used.But, this method oversimplification Fare Collection System, have ignored the trip requirements of different passenger, i.e. demand elasticity, it is common that cause the main cause of serious financial burden to enterprises of public transport.Luckily, after, along with the use that is widely popularized of bus IC card, multistage ticket prepares to be applied in each big city.Compared to flat fare, it can reflect " the true expense " that passenger goes on a journey more, embody higher social equity.But advantage is only more than long-distance transport in the price elasticity of (1) short-distance transport；(2) quantity transported for long-distance exists more than in the case of short-distance transport two kinds.
When determining the Bi-level Programming Models describing relation between passenger, government and enterprise, after in upper layer model, Pricing Game between government and enterprise determines public transport ticket molding formula and pricing strategy, passenger can make a response according to the strategy of policymaker in underlying model, object of study includes: public traffic network describes, trip generalized cost, conllinear problem, the nonadditivity of admission fee, and the routing strategy of passenger.Therefore, upper strata public transport price and subsidy model can be delivered to by Bi-level Programming Models, Transit assignment and other correlated results, the major parameter good and bad as evaluating upper layer model.
For the defect solved in existing public transport ticket charging structure in single fare and multi discount; promote passenger to go on a journey and desalinate the consideration to path sorting charge; more pay close attention to the efficiency of trip route; the present invention proposes the city bus optimum charging structure of a kind of origin and destination air line distance of going on a journey based on passenger; this charging structure has desalinated the trip route of passenger; i.e. admission fee is unrelated with the trip track of passenger or mileage, and only relevant with the air line distance of its beginning and the end website.This charging structure had both considered the trip distance of passenger, the most not with the actual trip distance of passenger for calculating standard, and it is translated into the air line distance between two websites, while playing based on distance charging structure advantage, passenger can be made again to desalinate when making routing strategy bus fee is considered, make the volume of the flow of passengers carry out uniform distribution in public traffic network, alleviate the passenger flow pressure of popular route, make transportation network farthest to be utilized.
Summary of the invention
Technical problem: the present invention provide a kind of consider government, enterprises of public transport and passenger's tripartite Game simultaneously determine method based on the go on a journey charge of city bus optimum charging structure based on origin and destination distance of origin and destination air line distance of passenger.
Technical scheme: the charge of the city bus optimum charging structure based on origin and destination distance of the present invention determines method, comprises the steps:
Step one: according to website and the route of Urban Transit Network, set up public traffic network topological diagram；
Step 2: according to the public traffic network topological diagram set up in described step one, determine the running time between the air line distance between all websites that public bus network to be fixed a price and this circuit are comprised, departure frequency, quantity of dispatching a car hourly, website, determine that this circuit runs fixed cost C once from origin-to-destination0, operation cost C1, relevant to the flow cost C that blocks up2, determine public transport regulation cost CRAnd the potential a maximum demand in regulation profit margin r, and public traffic network topological diagramDiscrete parameter β, time value λ of passenger and the passenger sensitivity β to minimum travel cost；
Step 3: the parameter in addition to " running time between air line distance between all websites, departure frequency, adjacent sites " determined in described step 2 is substituted into the following city bus optimum charging structure Bi-level Programming Models being made up of upper layer model, constraints and underlying model:
Upper layer model:
Constraints:
τmin≤τ≤τmax
Underlying model:
Wherein,WithRepresent origin and destination admission fee and flow, T to using path k in w respectivelylAnd NlRepresent that route L has travelled the total time of full journey and quantity of dispatching a car hourly, q respectivelywRepresent origin and destination to the passenger flow demand between w,Represent average fare, τminAnd τmaxRepresent the upper and lower limit of admission fee respectively,Represent origin and destination in w use path k generalized cost,Expression origin and destination are to using the time of vehicle operation of section s, waiting time and admission fee in the k of path between w respectively,Represent that origin and destination are to the probability of use path k, S between wwRepresent that passenger expects minimum Trip Costs；
Step 4: the running time between air line distance between all websites that will determine in described step 2, departure frequency, adjacent sites substitutes into Revised genetic algorithum, solve described city bus optimum charging structure Bi-level Programming Models, finally give optimum toll project based on origin and destination distance.
Further, in inventive method, in described step 4, the idiographic flow of Revised genetic algorithum is:
Step 1: one group of parameter value in public transport charge structural equation is defined as body one by one, one population of all individual compositions, determine the interval of each parameter in the individual number in initial population, maximum evolution number, crossover probability, mutation probability, maximum evolutionary generation, and public transport charge structural equation；
Step 2: arranging evolutionary generation is zero, randomly generate initial population, described initial population is substituted into underlying model, calculate each individual corresponding path flow and demand in initial population respectively, and result of calculation is substituted into upper layer model, calculate the upper strata target function value of each individuality respectively；
Step 3: each individuality is selected, intersects, makes a variation, obtains progeny population；
Step 4: described progeny population is substituted into underlying model, calculate each individual corresponding path flow and average fare in progeny population respectively, it is judged that the constraint of the following two in constraints during whether each individuality meets city bus optimum charging structure Bi-level Programming Models in progeny population:
τmin≤τ≤τmax
If meeting, then entering step 5, if being unsatisfactory for, then returning step 3；
Step 5: the path flow corresponding to the progeny population individuality of satisfied constraint and demand being substituted into upper layer model, calculates the upper strata target function value of each individuality, evolutionary generation increases by 1；
Step 6: if evolutionary generation reaches maximum evolutionary generation, then stop circulation, the individuality corresponding to the target function value of optimum upper strata now is optimum toll project, otherwise returns step 3.
Further, in inventive method, the public transport charge structural equation in described step 1 is:
Wherein,The admission fee of the section s between putting for upper two transfers of path k,And τdBe respectively the standing part in charging structure room and variable part parameter, d (i, j) be in the s of section starting point i to the air line distance of terminal j.
Owing to passenger is not equal to the expense sum of each public transportation road section in this path from the expense of origin-to-destination, i.e. passenger's travel cost has nonadditivity, so the present invention is by bus traveler assignment method based on path, and unconventional link based algorithm, the present invention has considered the rights and interests game between each public transport participant by introducing game theory.
Public transport charge mode can be divided into traditional flat fare and multistage charging structure.The factors such as flat fare and class of track, type of vehicle, ride circuit length and operation cost are the most unrelated, thus easily cause the unfair sense of passenger on short trips, thus cause the reduction that passenger on short trips measures, and conevying efficiency also decreases.Multistage ticket system can be further divided into again by distance charge, by region charge, temporally charge with by service charge.Although multistage ticket system can solve the problem that flat fare cannot meet the limitation of multiple trip requirements, but is only having the advantage that the price elasticity of (1) short-distance transport is more than long-distance transport in the following two cases；(2) quantity transported for long-distance is more than short-distance transport.As can be seen here, flat fare is more suitable for the small and medium cities of short distance trip, and multistage ticket system is suitable for the large size city of trip requirements more horn of plenty.In order to solve uniform pricing method and the defect of multistage ticket in existing public transport ticket structure, embody the elastic demand that traffic path is selected by different user, the present invention utilizes dual layer resist theoretical, from composition and the Industrial Features of urban public tranlport system, analyze public transport price and the feature of subsidy and principle, the comprehensive quality analyzing existing price and subsidy method, using Transit assignment model as describing the main method that passenger selects in different public transport ticket results and horizontal route.Again centered by Bi-level Programming Models, public transport price and subsidy model are combined with Transit assignment, set up city bus optimal fare charging structure Optimized model, simulation ticket price structure and the level impact on passenger's routing strategy, thus the determination evaluated for urban public transport optimal pricing and subsidy provides foundation.
Beneficial effect: the present invention compared with prior art, has the advantage that
Based on existing urban public transport ticket molding formula, invention proposes a kind of ticket price structure based on origin and destination distance.Under this ticket system, admission fee is determined by the air line distance of passenger getting on/off website.And demonstrate this ticket price structure with example and there is flat fare and the common feature of multistage ticket system, i.e. compared with flat fare, that takes into account the actual cost of passenger's trip, the trip requirements that passenger is different can be met, the most fair；Compared with multistage ticket system, only consider that the distance of origin and destination can desalinate the admission fee impact on passenger's Path selection, make the volume of the flow of passengers of popular public bus network be shunted.
In order to try to achieve the optimum toll rate of ticket price structure, the present invention proposes and a kind of considers government, enterprise and the Bi-level Programming Models of passenger's tripartite Game.In existing public transport optimal fare model, the tripartite Game of government, enterprise and passenger is generally chosen both and is considered respectively, the most only considers government and passenger or enterprise and passenger.In the present invention, game between government and enterprise is defined as trust-Agent Game, i.e. government entrusts enterprises of public transport to provide bus service, and by being equipped with incentive mechanism, retrains and induce succedaneum (enterprises of public transport) to make the strategy of beneficially principal (government).When, after admission fee strategy decision, passenger can make a response according to trip requirements.In economic field, Stackelberg game is applicable to describe the hierarchical relationship participating in theme: upper strata play a leading role first carry out decision-making for leader, lower floor lay under tribute by upper strata affected for follower.In the present invention, government and bus operation enterprise are collectively as senior level leader person, and passenger is lower floor follower.In upper layer model, government and enterprise carry out public transport price and the decision-making of subsidy by trust-Agent Game, it is also contemplated that the reaction of lower floor passenger simultaneously, define the master slave relation influencing each other, mutually restricting between the most upper and lower layer.
Compared with traditional flat fare, this charging structure considers the feature from different passenger's trip distances；Compared with multistage ticket system, charging structure is not the most with the actual trip distance of passenger for calculating standard, and it is translated into the air line distance between two websites, while playing based on distance charging structure advantage, passenger can be made again to desalinate when making routing strategy bus fee is considered, make the volume of the flow of passengers carry out uniform distribution in public traffic network, alleviate the passenger flow pressure of popular route, make transportation network farthest to be utilized.
Accompanying drawing explanation
Fig. 1 is Euclidean distance explanatory diagram.
Fig. 2 is the public traffic network represented with bus routes and section.
Fig. 3 is 9 node public traffic network schematic diagrams.
Detailed description of the invention
Below in conjunction with example and Figure of description, the present invention is further illustrated.
This part content is further elucidated with the present invention in conjunction with the embodiments, it should be understood that these embodiments are merely to illustrate the present invention rather than limit the scope of the present invention, after having read the present invention, the amendment of the various equivalent form of values that those skilled in the art tackle the present invention all falls within the application claims limited range.
Step one: according to website and the route of Urban Transit Network, set up public traffic network topological diagram；
Assuming that a public traffic network G=(N, L) being closely connected represents, wherein N and L is the set of bus station and public bus network respectively.Being different from section network, bus station is connected by a plurality of public bus network.Therefore, a public traffic network (see Fig. 1) can change into a route segment network (see b in Fig. 2).Wherein, O, X, Y, D represent bus station, are public transit vehicle fixing websites stopped in running, for passenger loading, get off and change to.Public bus network refers to vehicle and the set of other stop websites in a fixing bus operation circuit.As it can be seen, circuit 2 can be expressed as L2: O, X, Y, circuit 1 can be expressed as L1: O, D.On public bus network, the line between continuous two bus stations is referred to as public transportation road section.When transit assignment, the concept of introducing path section describes conllinear problem, and such as XY route segment can be expressed asBetween the origin and destination of passenger's trip, the collection of taken pubic transport circuit and transfer website is collectively referred to as path, can be expressed as from a paths of an O a to D:
Example public traffic network topology is as it is shown on figure 3, have origin and destination to (i.e. N in figure1-N9), 9 bus station (N1, N2, N3, N4, N5, N6, N7, N8And N9) and 5 public bus network (L1, L2, L3, L4And L5)。
Step 2: according to the public traffic network topological diagram set up in described step one, determine the running time between the air line distance between all websites that public bus network to be fixed a price and this circuit are comprised, departure frequency, quantity of dispatching a car hourly, website, determine that this circuit runs fixed cost C once from origin-to-destination0, operation cost G1, relevant to the flow cost C that blocks up2, determine public transport regulation cost CRAnd the potential a maximum demand in regulation profit margin r, and public traffic network topological diagramDiscrete parameter θ, time value λ of passenger and the passenger sensitivity β to minimum travel cost；
Example public traffic network inputs data as shown in table 1.For simplicity, it is assumed that all these routes have fixing frequency, operation cost and the travel time.Other parameters are: origin and destination are to N1-N9Between potential a maximum demandBe 1,000 people/hour, β takes 7, and λ takes 0.3, and θ takes 0.9, CRTaking 3.46, r takes 6%.
Table 1 public bus network information
Step 3: the parameter in addition to " running time between air line distance between all websites, departure frequency, adjacent sites " determined in described step 2 is substituted into the city bus optimum charging structure Bi-level Programming Models set up by this step.
Set up city bus charging structure Bi-level Programming Models, solve the optimum toll rate of different charging structure.Its at the middle and upper levels model be trust-Agent Game, government and the enterprises of public transport process at Public Transport Pricing Yu subsidy is described；Lower floor is that public transport based on Logit distributes model, describes passenger's reflection to different charging structures.The present invention uses trust-Agent Game to the relation describing between government and enterprise, and wherein government is principal, and enterprise is succedaneum.The operation and management of public transit system is directly participated in, in the environment of government and enterprise are in asymmetrical information due to enterprises of public transport.And in price with the gambling process of subsidy strategy, government department is contemplated to be social welfare maximum, and enterprises of public transport are contemplated to be maximum profit.So enterprises of public transport would generally select to make the maximized strategy of number one, and this strategy is generally desired for cost with sacrifice government.So government i.e. can subsidize by arranging incentive mechanism, retrain and induce enterprises of public transport to make the strategy of beneficially government.
In upper layer model, turning to object function with enterprises of public transport's Income Maximum, wherein income refers to ticket income and the subsidy summation determined according to business circumstance.Wherein in the formulation entrusting acting body present fare level scope and Price Regulation of government.Introduce each ingredient of upper layer model in detail below.
The profit of enterprise generally represents by the difference of ticket income with operation cost:
In formula, Section 1 is the charge income of enterprises of public transport.Section 2 represents operation cost, including fixed cost C0, variable cost C1And the block up cost C relevant to flow2。Represent that origin and destination, to the flow of path k between w, can be tried to achieve by underlying model.
The primary function of government is to ensure that admission fee is in the range of the most reasonably.On the one hand the lower limit of fare level to be specified, ensures that enterprise obtains rational ticket income；On the other hand the upper limit of admission fee to be controlled so that it is major part civic, city trip requirements can be met.So upper layer model constraints for ensure ticket price structure need to one reasonably in the range of:
τmin≤τ≤τmax (2)
Chinese Financial Subsidy Policies based on enterprises of public transport's operation situation is the most necessary, because it at least can ensure that normal operation and the sustainable development of enterprises of public transport, enterprises of public transport also can be encouraged to improve work efficiency, it is provided that better service simultaneously.Therefore, by benefit simultaneously the financial subsidies of enterprises of public transport and passenger can realize social benefit maximize.According to the relevant regulations of China's city bus administrative law, the subsidy total value of whole public traffic network is that mathematic(al) representation is as follows:
In formula, CRIt is according to the regulation cost that the previous year, financial condition determined by traffic and transportation sector.Q is the bus service amount (passenger traffic volume) in target year.R is that enterprises of public transport are in order to ensure the public transport regulation profit margin of sustainable development.It is average fare, qw(τ) being the total volume of the flow of passengers in public traffic network, the two amount all will solve in underlying model and draw.If the optimal fare level of certain ticket price structure is higher, then there will be public traffic network average fareMore than regulation cost CRSituation, i.e. subsidy total value S ＜ 0, it is clear that this situation is irrational in reality.Based on considerations above, in upper layer model in addition to retraining the standing part of each ticket price structure and variable part, the average fare level also tackling network retrains, i.e.
In sum, the complete expression of upper layer model is
Meet and retrain:
τmin≤τ≤τmax (7)
In formula, the Transit assignment i.e. underlying model of problem based on Logit that q (τ) and h (τ) is defined by above formula (9)-(15) is given.
The method using Stochastic Traffic Assignment is obtained the concrete outcome of Transit assignment by underlying model.Owing to there are variable and immutable two parts in non-linear ticket price structure, the through expense directly collected from passenger getting on/off website is often not equal to the expense sum in each several part section, path.Use Logit traffic assignation method based on path the most herein.
Assume the broad sense traveling efficacy of each section s on the k of pathBe made up of three parts: by hour in units of in way time and waiting time, and the bus fee in units of unit.The detecting period of passenger obeys Gumbel distribution.At this moment, when cost route set based on time correlation is determined, path expenseCan be obtained by the section total utility superposition calculation combining travel time and currency travel cost, shown in following (6) formula.Wherein travel time and waiting time are converted into monetary unit by time value parameter, then are combined with the ticket applied.Assume the stochastic error in the random traveling efficacy of passengerSeparate, and obey Gumbel distribution.
In formula:Generalized cost (or effectiveness) function of path k；
Public transportation road section s in the way time in the k of path；
The waiting time of public transportation road section s in the k of path；
The admission fee expense of public transportation road section s in the k of path；
Stochastic error；
The time value of λ passenger.
Theoretical according to maximization of utility, the probability of Path selection can be given by following Logit formula:
In formula, θ is discrete parameter.θ value is the highest, and the information that in public traffic network, passenger perceives is the most.
In view of the ridership in ticket price structure can be produced impact, in public traffic network, the elastic demand of passenger also has to be analyzed.One origin and destination is to the total passenger demand q between wwCan be by a continuous print, anticipated travel cost S of monotone decreasingwFunction determine, namely:
qw=Dw(Sw) (11)
Wherein, it is contemplated that minimum travel cost SwCan be calculated as follows:
In formula,Being total travel cost of path k, it can be calculated in underlying model.
Usually, demand function is the function of a continuous monotone decreasing.In conventional research, form many employings exponential form of demand function
Or linear forms
In formula:Origin and destination are to the potential a maximum demand between w；
β passenger's sensitivity to minimum travel cost.
Therefore, required on the upper layer model Road footpath k volume of the flow of passengers can be calculated as follows:
Step 4: the running time between air line distance between all websites that will determine in described step 2, departure frequency, adjacent sites substitutes into Revised genetic algorithum, solve described city bus optimum charging structure Bi-level Programming Models, finally give optimum toll project based on origin and destination distance.
Bi-level Programming Models has proved to be NP-hard problem, and therefore, the present invention will use a Revised genetic algorithum to solve this Bi-level Programming Models.The thought of this algorithm predominantly, first randomly generates initial population in the feasible set of upper strata plan model, each chromosome correspondence one public transport fares function and its corresponding ticket price structure in population.For different ticket price structure, two different genes are used for representing fixed charge therein and variable expenses.Specifically comprise the following steps that
Step 1: one group of parameter value in public transport charge structural equation is defined as body one by one, one population of all individual compositions, determine the individual number in initial population be 50, maximum evolution number be 50, crossover probability be 0.9, mutation probability be 0.9, and the interval of each parameter in public transport charge structural equationτd∈ [0,2]；
Step 2: arranging evolutionary generation is zero, randomly generate initial population, described initial population is substituted into underlying model, calculate each individual corresponding path flow and demand in initial population respectively, and result of calculation is substituted into upper layer model, calculate the upper strata target function value of each individuality respectively；
Step 3: each individuality is selected, intersects, makes a variation, obtains progeny population；
Step 4: described progeny population is substituted into underlying model, calculate each individual corresponding path flow and average fare in progeny population respectively, it is judged that the constraint of the following two in constraints during whether each individuality meets city bus optimum charging structure Bi-level Programming Models in progeny population:
τmin≤τ≤τmax
If meeting, then entering step 5, if being unsatisfactory for, then returning step 3；
Step 5: the path flow corresponding to the progeny population individuality of satisfied constraint and demand being substituted into upper layer model, calculates the upper strata target function value of each individuality, evolutionary generation increases by 1；
Step 6: if evolutionary generation reaches maximum evolutionary generation, then stop circulation, the individuality corresponding to the target function value of optimum upper strata now is optimum toll project, otherwise returns step 3.
Finally give city bus optimum charging structure based on origin and destination distance:
Main parameter in example public traffic network is as shown in table 2,
Above-described embodiment is only the preferred embodiment of the present invention; it is noted that, for those skilled in the art; under the premise without departing from the principles of the invention; some improvement and equivalent can also be made; the claims in the present invention are improved and technical scheme after equivalent by these, each fall within protection scope of the present invention.

Claims (3)

1. the charge of a city bus optimum charging structure based on origin and destination distance determines method, it is characterised in that The method comprises the following steps:
Step one: according to website and the route of Urban Transit Network, set up public traffic network topological diagram；
Step 2: according to the public traffic network topological diagram set up in described step one, determines public bus network to be fixed a price and is somebody's turn to do Row between air line distance between all websites that circuit is comprised, departure frequency, quantity of dispatching a car hourly, website Sail the time, determine that this circuit runs fixed cost C once from origin-to-destination0, operation cost C1, with flow phase The cost C that blocks up closed2, determine public transport regulation cost CRAnd in regulation profit margin r, and public traffic network topological diagram Potential a maximum demandDiscrete parameter β, time value λ of passenger and the passenger sensitivity to minimum travel cost β；
Step 3: by described step 2 determines except " air line distance between all websites, departure frequency, adjacent Running time between website " outside parameter substitute into the following city that is made up of upper layer model, constraints and underlying model City's public transport optimum charging structure Bi-level Programming Models:
Upper layer model:
max τ Z ( τ , q ( τ ) , h ( τ ) ) = Σ w ∈ W τ k w h k w - [ Σ l ∈ L ( C 0 + C 1 · T l · N l ) + Σ w ∈ W C 2 h k w ] + Σ w ∈ W [ τ c r ( 1 + r ) - τ ‾ ] · q w ( τ )
Constraints:
q w = Σ k ∈ K h k w
τmin≤τ≤τmax
C R ( 1 + r ) - τ ‾ ≥ 0 ;
Underlying model:
c k w = Σ w ∈ W Σ k ∈ K Σ s ∈ S ( t s , k w + w s , k w + λτ s , k w )
P k w = exp ( - θc k w ) Σ k ∈ K exp ( - θc k w )
S w = E [ min k ∈ K ( c k w ) ] = - 1 θ ln Σ k ∈ K exp ( - θc k w )
q w = q w 0 - βS w
h k w = q w P k w
Wherein,WithRepresent origin and destination admission fee and flow, T to using path k in w respectivelylAnd NlTable respectively Show that route L has travelled the total time of full journey and quantity of dispatching a car hourly, qwRepresent that origin and destination are to the passenger flow demand between w Amount,Represent average fare, τminAnd τmaxRepresent the upper and lower limit of admission fee respectively,Represent that origin and destination make in w With the generalized cost of path k,Represent that origin and destination are to using the car of section s in the k of path between w respectively Running time, waiting time and admission fee,Represent that origin and destination are to the probability of use path k, S between wwExpression is taken advantage of The minimum Trip Costs of visitor's expectation；
Step 4: the air line distance between all websites that will determine in described step 2, departure frequency, adjacent sites Between running time substitute into Revised genetic algorithum, solve described city bus optimum charging structure Bi-level Programming Models, Finally give optimum toll project based on origin and destination distance.
The charge of city bus optimum charging structure based on origin and destination distance the most according to claim 1 determines Method, it is characterised in that in described step 4, the idiographic flow of Revised genetic algorithum is:
Step 1: one group of parameter value in public transport charge structural equation is defined as body one by one, all individual compositions one Individual population, determines the individual number in initial population, maximum evolution number, crossover probability, mutation probability, maximum evolution The interval of each parameter in algebraically, and public transport charge structural equation；
Step 2: arranging evolutionary generation is zero, randomly generates initial population, substitutes into underlying model by described initial population, Calculate each individual corresponding path flow and demand in initial population respectively, and result of calculation substituted into upper layer model, Calculate the upper strata target function value of each individuality respectively；
Step 3: each individuality is selected, intersects, makes a variation, obtains progeny population；
Step 4: described progeny population substitutes into underlying model, calculates each individual corresponding road in progeny population respectively Run-off and average fare, it is judged that in progeny population, whether each individuality meets city bus optimum charging structure bilayer rule The following two constraint drawn in model in constraints:
τmin≤τ≤τmax
C R ( 1 + r ) - τ ‾ ≥ 0 ;
If meeting, then entering step 5, if being unsatisfactory for, then returning step 3；
Step 5: the path flow corresponding to the progeny population individuality of satisfied constraint and demand are substituted into upper layer model, meter Calculating the upper strata target function value of each individuality, evolutionary generation increases by 1；
Step 6: if evolutionary generation reaches maximum evolutionary generation, then stop circulation, optimum upper strata object function now Individuality corresponding to value is optimum toll project, otherwise returns step 3.
The charge of city bus optimum charging structure based on origin and destination distance the most according to claim 2 determines Method, it is characterised in that the public transport charge structural equation in described step 1 is:
τ s , k d = τ d 0 + τ d · d ( i , j )
Wherein,The admission fee of the section s between putting for upper two transfers of path k,And τdIt is respectively charging structure room In standing part and variable part parameter, d (i, j) be in the s of section starting point i to the air line distance of terminal j.
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