CN107330716A - A kind of customization public transport pricing method for considering system optimal - Google Patents
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Abstract
The invention discloses a kind of customization public transport pricing method for considering system optimal, including step：Obtain foundation of planning data；Regular public traffic, customization public transport, the generalized travel cost function of car are set up respectively；Lower floor's multimode Stochastic User Equilibrium Assignment Model of equal value is set up according to multimode transportation network equilibrium condition, it is considered to which system optimal sets up upper layer model, so as to build Bi-level Programming Models to describe the customization public transport pricing problem in the case of system optimal；The Bi-level Programming Models being made up of upper strata plan model and lower floor's plan model are solved, the customization public transport optimal pricing in the case of system optimal is obtained.The present invention is more scientific compared to traditional pricing model in the past, can effectively reduce system synthesis sheet, attract traveler to use bus trip by science price, can effectively improve public transport share rate, reduce car share rate.
Description
Technical field
The present invention relates to field of traffic control, more particularly to a kind of customization public transport pricing method for considering system optimal.
Background technology
It is a kind of mode of transportation based on internet to customize public transport, since 2013, in China, especially north, it is upper,
Extensively, the big city such as deep has obtained very fast development.Customization public transport follows the service original of " determine people, fixed point, timing, price, determine car "
Then, quality services are provided with economic price, with stronger attraction.Development customization public transport, is conducive to making " guarantee public affairs
The urban public tranlport system of friendship+high-quality public transport ", promotes the structure in " public transport city ".
Research at present both at home and abroad to customizing public transport fares formulating method is less, is generally to customize bus operation cost in accounting
On the basis of its profit and loss is discussed, with this determination admission fee.Such method is although simple to operation, but have ignored customization public transport " accurate public
The property of traffic altogether ", the optimal angle of whole system is not based oneself upon and is fixed a price, and causes traffic of the result to promotion traveler of fixing a price
Mode, which is shifted, not to be acted on, in some instances it may even be possible to produce counter productive.Huang Qi is equal to paper《Customization public transport based on Bi-level Programming Models
Price making》In (be published in《Chinese science and technology paper is online》, 2016), determine that customization is public by target of social welfare maximization
Hand over admission fee, it is contemplated that mutual transfer and influence between each mode, but its social welfare considered is difficult to obtain in practical operation
Real data is taken, the practicality and autgmentability of method is defined.
The content of the invention
It is an object of the invention to the shortcoming and deficiency for overcoming prior art, there is provided a kind of customization for considering system optimal is public
Pricing method is handed over, by customizing the Rational Development of public transport Coordination of Pricing Traffic Systems, customization public transport has been given play to reduction small
The effect of automobile trip, with actual promotional value.
The purpose of the present invention is realized by following technical scheme：
A kind of customization public transport pricing method for considering system optimal, comprises the following steps：
S1, acquisition foundation of planning data, including：OD is to requirement forecasting data, regular public traffic and customization public transport construction operation
Cost data and road network related data；
S2, the broad sense Trip Costs function for setting up regular public traffic, customization public transport and car respectively；
S3, lower floor's plan model set up according to multimode transportation network equilibrium condition：Multimode random user of equal value is put down
Weigh model；Consider that system optimal sets up upper strata plan model；So as to build Bi-level Programming Models to describe system optimal situation
Under customization public transport pricing problem；
S4, the Bi-level Programming Models being made up of upper strata plan model and lower floor's plan model are solved, obtain system
Customization public transport optimal pricing under optimal situation.
It is preferred that, the OD includes total travelling OD amount predicted value between each OD pairs to requirement forecasting data, from the volume of traffic
Prediction data obtains OD to requirement forecasting data.
It is preferred that, the regular public traffic and customization public transport construction operation cost data include regular public traffic, customization public transport base
Infrastructure construction cost, operation maintenance expense, time mechanism, regular public traffic departure frequency, regular public traffic seating capacity, regular public traffic
Compartment standing room area, regular public traffic average speed and customization public transport average speed；Regular public traffic is resulted in by market survey
With customization public transport construction operation cost data.
It is preferred that, the road network related data includes road section length, free flow running time, the traffic capacity and impedance letter
Number.
It is preferred that, regular public traffic, customization public transport, the broad sense Trip Costs function of car are set up in step S2, comprising such as
Lower step：
S2-1 calculates broad sense Trip Costs functions of the OD to the regular public traffic trip between (r, s)Including the travel time
Cost, waiting time cost, uncomfortable cost and admission fee cost：
In formula, β is traveler long-run cost rate；
For regular public traffic go on a journey journey time,lrsIt is OD to the distance between (r, s)；vbFor regular public traffic
Trip average speed；
For regular public traffic go on a journey waiting time,F is regular public traffic departure frequency；
It is crowded with detecting period change type for in-car,
For in OD amounts of the OD to selection regular public traffic trip mode between (r, s)；sbFor seating capacity in regular public traffic compartment；λ is compartment
Standing room area；α1=0.021；α2=1.82；
For regular public traffic admission fees of the OD to (r, s)；
S2-2 calculates broad sense Trip Costs functions of the OD to the customization bus trip between (r, s)Including the travel time
And admission fee：
In formula, β is traveler long-run cost rate,To customize bus trip journey time,lrsFor OD pairs
The distance between (r, s), vdFor customization bus trip average speed；
For in OD to the customization public transport fares on (r, s)；
S2-3 calculates broad sense Trip Costs functions of the OD to (r, s) upper pathway k car tripDuring including trip
Between, fuel oil takes：
In formula, β is traveler long-run cost rate,The trip journey time for being car on the k of path, For the relation variable in section and path, if section a is on the kth paths between (r, s), thenOtherwise,A is the set in all sections；
G is that car unit mileage fuel oil takes；lrs,kFor distances of the OD to the kth paths between (r, s)；
For journey time of the car on a of section, it can be calculated using BPR functions, i.e.,：
In formula,For section a free flow running time；xaFor section a car transportation amount, For path k car transportation amount；caFor road section capacity；R、S、KrsSet, the set of terminal of starting point are represented respectively
With OD to the set of paths between (r, s)；
OD is calculated to the broad sense Trip Costs of the car trip in all paths between (r, s), minimum value is taken as OD pairs
The minimum broad sense Trip Costs of the car trip of (r, s)：
It is preferred that, the step of upper strata plan model is set up in step S3 includes：
To realize system optimal as target making admission fee, traffic system under fixed demand is optimal to be equivalent to system synthesis
This minimum, system synthesis sheet includes operation totle drilling cost and traveler totle drilling cost, and its object function is represented by：
In formula, Z represents system synthesis sheet, i.e. traveler totle drilling cost and operation totle drilling cost sum；Represent in OD to (r, s)
Between selection customization bus trip mode travel amount；laRepresent section a length；Public transport company is customized to (r, s) for OD
Fixation operation cost；The average variable specific discharge operation cost of public transport company is customized to (r, s) for OD；For OD pairs
The fixation operation cost of (r, s) regular public traffic company；For average variable unit mileages of the OD to (r, s) regular public traffic company
Operation cost；Represent operation mileages of the OD to regular public traffic between (r, s)；F is regular public traffic departure frequency.
It is preferred that, the step of lower floor's plan model is set up in step S3 includes：
By assuming：Car trip optimizing paths meet the stochastic user equilibrium criterion based on Logit, car side
Formula trip meets stochastic user equilibrium condition, i.e. OD and the car trip amount that path k is selected between (r, s) can be calculated by following formula：
In formula,Refer to OD to car trip amount total between (r, s)；
By assuming：Traveler in network can only be arrived at by three kinds of modes, i.e., regular public traffic, customization public transport and
Car, the three kinds of trip modes corresponded respectively in set M={ b, d, c }, the probability that three kinds of modes are selected obeys Logit moulds
Type calculation formula, Passenger Traveling Choice meets Logit formula, i.e.,：
In formula,The probability of m class trip mode is selected (r, s) for OD；M class trip modes are selected to (r, s) for OD
Broad sense Trip Costs；QrsFor the OD OD amounts total to (r, s)；The OD amount of m class trip mode is selected (r, s) for OD；θ is anti-
Mirror understanding difference of the passerby to each path disutility；η reflects traveler to regular public traffic, three kinds of sides of customization public transport and car
The understanding difference of formula disutility；
By discrete Choice Theory, OD is to the minimum broad sense Trip Costs of expectation between (r, s)：
The analysis described according to network, sets up the mathematical programming model of following multimode Stochastic User Equilibrium of equal value：
s.t.
xa≤ca
In formula, Z represents system synthesis sheet, i.e. traveler totle drilling cost and operation totle drilling cost sum；
Above-mentioned first be constrained to OD flows model split conservation constraints；Second be constrained to car flow path
Select conservation constraints；3rd be constrained to three kinds of mode flows nonnegativity restrictions；4th is constrained to car path flow
Nonnegativity restrictions；5th be constrained to link flow capacity consistency condition.
It is preferred that, using the strong genetic algorithm of global convergence in upper strata plan model and lower floor's plan model in step S4
Between iterate to approach the optimal solution of Bi-level Programming Models, wherein, underlying model is solved by sequential quadratic programming algorithm.
It is preferred that, step S4 is comprised the following steps that：
4-1 is initialized：The encoding scheme of genetic algorithm chromosome is designed, parameter is determined；Random generation customization public transport fares,
And lower floor's plan model kind solution flow is substituted into, S group chromosomes are obtained, initial population P is constituted0；
4-2 object functions are calculated：Upper strata desired value Z is solved to S group chromosomes respectivelys, and record maximum target value and its
Homologue；
4-3 stop technologies：If evolutionary generation gen reaches maximum evolutionary generation maxgen, stop algorithm, decoding dyeing
Admission fee and flow in body, output optimal solution；Otherwise step 4-4 is carried out；
4-4 carries out genetic manipulation：Selection is performed, intersects and makes a variation, and the customization public transport fares after evolution are substituted into lower floor
Plan model, solves flow, constitutes new population Pgen+1；Return to step 4-2.
The present invention compared with prior art, has the following advantages that and beneficial effect：
The present invention considers customization public transport, regular public traffic and the class trip mode of car three joint, passes through system synthesis sheet
(traveler cost with network operator's totle drilling cost) this minimum target determines reasonably to customize public transport fares, utilizes the change of its admission fee
More, transfer of the Private Traffic to public transport is realized, alleviates urban traffic pressure.The present invention is compared to traditional pricing model in the past more
Tool is scientific, can effectively reduce system synthesis sheet.Attract traveler to use bus trip by science price, public affairs can be effectively improved
Share rate is handed over, car share rate is reduced；In the financial mode of public transport, guiding government is given necessarily to customization enterprises of public transport
Operation subsidy, so as to reach the mesh of system optimal, reduce system synthesis sheet, promote the sustainable development of traffic system, have
Stronger promotional value.
Brief description of the drawings
Fig. 1 is the flow chart of embodiment method；
Fig. 2 is embodiment network.
Embodiment
With reference to embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not limited
In this.
A kind of customization public transport pricing method for considering system optimal, with regular public traffic, three kinds of friendships of customization public transport and car
The logical mode and multimode urban road network deposited is Research foundation, sets up Bi-level Programming Models to study the price of customization public transport
Problem.Upper strata pricing decision model is built by target of system optimal, lower floor is multimode Stochastic User Equilibrium Assignment Model of equal value.
Model is solved using genetic algorithm and sequential quadratic programming algorithm (SQP).Specifically include following steps：
1st, foundation of planning data is obtained, includes the data of three aspects：OD (Origin Destination) is to requirement forecasting
Data, regular public traffic and customization public transport construction operation cost data, road network related data；
The OD includes total travelling OD amount predicted value between each OD pairs to requirement forecasting data, from traffic volume forecast data
OD is obtained to requirement forecasting data.
The regular public traffic and customization public transport construction operation cost data include regular public traffic, customization public transport infrastructure construction
If expense, operation maintenance expense, time mechanism, regular public traffic departure frequency, regular public traffic seating capacity, regular public traffic compartment standing room
Area, regular public traffic average speed and customization public transport average speed.Regular public traffic is resulted in by market survey and customization is public
Hand over construction operation cost data.
The road network related data includes road section length, free flow running time, the traffic capacity and impedance function.
2nd, regular public traffic, customization public transport, the broad sense Trip Costs function of car are set up respectively；
Regular public traffic, customization public transport, the broad sense Trip Costs function of car are set up, is comprised the following steps：
2-1 calculates broad sense Trip Costs of the OD to the regular public traffic trip between (r, s)Including travel time cost,
Waiting time cost, uncomfortable cost and admission fee cost (being assumed to constant to simplify in problem, text)：
In formula, β is traveler long-run cost rate；
For regular public traffic go on a journey journey time,lrsIt is OD to the distance between (r, s)；vbFor regular public traffic
Trip average speed；
For regular public traffic go on a journey waiting time,F is regular public traffic departure frequency；
It is crowded with detecting period change type for in-car,
For in OD amounts of the OD to selection regular public traffic trip mode between (r, s)；sbFor seating capacity in regular public traffic compartment；λ is compartment
Standing room area；α1=0.021；α2=1.82；
For regular public traffic admission fees of the OD to (r, s).
2-2 calculates broad sense Trip Costs of the OD to the customization bus trip between (r, s)Including travel time and ticket
Valency：
In formula,To customize bus trip journey time,vdFor customization bus trip average speed；
For in OD to the customization public transport fares on (r, s).
2-3 calculates broad sense Trip Costs of the OD to (r, s) upper pathway k car tripIncluding travel time, combustion
It is oily to take：
In formula,The trip journey time for being car on the k of path, For section and path
Relation variable, if section a is on the kth paths between (r, s), thenOtherwise,A is all sections
Set；
G is that car unit mileage fuel oil takes；lrs,kFor distances of the OD to the kth paths between (r, s)；
For journey time of the car on a of section, it can be calculated using BPR functions, i.e.,：
In formula, xaFor section a car transportation amount, Handed over for path k car
Flux；For section a free flow running time；caFor road section capacity；R、S、KrsSet, the terminal of starting point are represented respectively
Set, and OD is to the set of paths between (r, s).
OD is calculated to the broad sense Trip Costs of the car trip in all paths between (r, s), minimum value is taken as OD pairs
The minimum broad sense Trip Costs of the car trip of (r, s)：
3rd, consider that system optimal sets up upper layer model；Underlying model is set up according to multimode transportation network equilibrium condition：Deng
The multimode Stochastic User Equilibrium Assignment Model of valency；The customization described so as to build Bi-level Programming Models in the case of system optimal is public
Hand over pricing problem.
Layer model in 3-1 foundation：Customization public transport is substantially a kind of " accurate public between public transport and Private Traffic
Traffic altogether " service, accordingly it is contemplated that subsidy form is guided by government or taken, to realize system optimal as target making
Admission fee.Traffic system under fixed demand is optimal to be equivalent to system synthesis sheet (including operation totle drilling cost and traveler totle drilling cost)
Minimum, its object function is represented by：
In formula, Z represents system synthesis sheet, i.e. traveler totle drilling cost and operation totle drilling cost sum；Represent in OD to (r, s)
Between selection customization bus trip mode travel amount；laRepresent section a length；Public transport company is customized to (r, s) for OD
Fixation operation cost；The average variable specific discharge operation cost of public transport company is customized to (r, s) for OD；For OD
To the fixation operation cost of (r, s) regular public traffic company；It is OD in the average variable unit of (r, s) regular public traffic company
Journey operation cost；Represent operation mileages of the OD to regular public traffic between (r, s)；F is regular public traffic departure frequency.
3-2 sets up underlying model：
By assuming：Car trip optimizing paths meet stochastic user equilibrium (SUE) criterion based on Logit, small
Automobile mode go on a journey meet stochastic user equilibrium condition, i.e. OD between (r, s) select path k car trip amount can be by following formula
Calculate：
In formula,Refer to OD to car trip amount total between (r, s).
By assuming：Traveler in network can only be arrived at by three kinds of modes, i.e., regular public traffic, customization public transport and
Car.For convenience of describing, these three trip modes are represented using set M={ b, d, c } in text.It is general that three kinds of modes are selected
Rate obeys Logit model calculation formulas, and Passenger Traveling Choice meets Logit formula, i.e.,：
In formula,The probability of m class trip mode is selected (r, s) for OD；M class trip modes are selected to (r, s) for OD
Broad sense Trip Costs；QrsFor the OD OD amounts total to (r, s)；The OD amount of m class trip mode is selected (r, s) for OD；θ is anti-
Mirror understanding difference of the passerby to each path disutility；η reflects traveler to regular public traffic, three kinds of sides of customization public transport and car
The understanding difference of formula disutility.
By discrete Choice Theory, OD is to the minimum broad sense Trip Costs of expectation between (r, s)：
The analysis described according to network, sets up the mathematical programming model of following multimode Stochastic User Equilibrium of equal value：
s.t.
xa≤ca
Model objective function formula is without intuitively economic meanings；First be constrained to OD flows model split conservation about
Beam；Second be constrained to car flow Path selection conservation constraints；3rd is constrained to three kinds of the non-of mode flow and breaks a promise
Beam；4th be constrained to car path flow nonnegativity restrictions；5th be constrained to link flow capacity consistency condition.
4th, the Bi-level Programming Models being made up of upper strata plan model and lower floor's plan model are solved, obtains system most
Customization public transport optimal pricing in the case of excellent.
The strong genetic algorithm of global convergence is used to iterate to approach bilayer between upper layer model and underlying model
The optimal solution of plan model, wherein, underlying model is solved by sequential quadratic programming algorithm (SQP).Comprise the following steps that.
4-1 is initialized.The encoding scheme of genetic algorithm chromosome is designed, parameter is determined；Random generation customization public transport fares,
And underlying model kind solution flow is substituted into, S group chromosomes are obtained, initial population P is constituted0。
4-2 object functions are calculated.Upper strata desired value Z is solved to S group chromosomes respectivelys, and record maximum target value and its
Homologue.
4-3 stop technologies.If evolutionary generation gen reaches maximum evolutionary generation maxgen, stop algorithm, decoding dyeing
Admission fee and flow in body, output optimal solution；Otherwise step 4-4 is carried out.
4-4 carries out genetic manipulation.Selection is performed, intersects and makes a variation, and the customization public transport fares after evolution are substituted into lower floor
Model, solves flow, constitutes new population Pgen+1.Return to step 4-2.
Specifically, the road network that the present embodiment is used is as shown in Figure 2.Road network includes 7 nodes altogether, 8 sections and two
OD is to (1,7) and (2,7), and dotted line represents public bus network (1-3-5-7 and 2-3-5-7), and solid line represents that car is feasible
Sail section.The trip situation of simulation commuting peak period, two OD pairs of fixed demand is 1200 people/hour and 1000 people/hour.
Road section length la, free flow running timeWith traffic capacity caAs shown in table 1, the parameter that embodiment is used such as table 2
It is shown.
The example road net data of table 1
The embodiment parameter value of table 2
Using matlab8.3 instrument implementation model algorithms, wherein, population scale takes 30, and maximum evolutionary generation takes 200, friendship
Fork probability and mutation probability take 0.95 and 0.05 respectively, solve the customization public transport optimal fare under system optimal, customize public transport public affairs
Profit, overall society cost, customization public transport share rate and system public transport share rate are taken charge of, concrete outcome is as shown in table 3.
The result of calculation of table 3
It is (6.9,5.1) using system optimal as the solution of target.As shown in Table 3, under system optimal situation, to reach that system goes out
Row totle drilling cost is minimum, and customization public transport fares are respectively 6.9 and 5.1, and overall society cost reaches 47978 yuan of minimum value, customizes public transport
Share rate reaches 65.22%.Current Guangzhou public transport share rate is 50%, and the regular public traffic of the system and customization public transport total score
Load rate reaches 72.4%, substantially increases public transport share rate.Summarize and understand, can to reduce system total for the pricing strategy of customization public transport
Cost, lifts public transport share rate.With actual promotional value, it is worthy to be popularized.
Above-described embodiment is preferably embodiment, but embodiments of the present invention are not by above-described embodiment of the invention
Limitation, other any Spirit Essences without departing from the present invention and the change made under principle, modification, replacement, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (9)
1. a kind of customization public transport pricing method for considering system optimal, it is characterised in that comprise the following steps：
S1, acquisition foundation of planning data, including：OD is to requirement forecasting data, regular public traffic and customization public transport construction operation cost
Data and road network related data；
S2, the broad sense Trip Costs function for setting up regular public traffic, customization public transport and car respectively；
S3, lower floor's plan model set up according to multimode transportation network equilibrium condition：Multimode Stochastic User Equilibrium mould of equal value
Type；Consider that system optimal sets up upper strata plan model；In the case of system optimal being described so as to build Bi-level Programming Models
Customize public transport pricing problem；
S4, the Bi-level Programming Models being made up of upper strata plan model and lower floor's plan model are solved, obtain system optimal
In the case of customization public transport optimal pricing.
2. customization public transport pricing method according to claim 1, it is characterised in that the OD includes to requirement forecasting data
Total travelling OD amount predicted value between each OD pairs, OD is obtained to requirement forecasting data from traffic volume forecast data.
3. customization public transport pricing method according to claim 1, it is characterised in that the regular public traffic and customization public transport are built
If operation cost data includes regular public traffic, customization public transport infrastructure construction expense, operation maintenance expense, time mechanism, often
Advise bus departure frequency, regular public traffic seating capacity, regular public traffic compartment standing room area, regular public traffic average speed and customization public transport
Average speed；Regular public traffic and customization public transport construction operation cost data are resulted in by market survey.
4. customization public transport pricing method according to claim 1, it is characterised in that the road network related data includes section
Length, free flow running time, the traffic capacity and impedance function.
5. customization public transport pricing method according to claim 1, it is characterised in that regular public traffic is set up in step S2, is determined
Public transport processed, the broad sense Trip Costs function of car, are comprised the following steps：
S2-1 calculates broad sense Trip Costs functions of the OD to the regular public traffic trip between (r, s)Including travel time cost,
Waiting time cost, uncomfortable cost and admission fee cost：
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In formula, β is traveler long-run cost rate；
For regular public traffic go on a journey journey time,lrsIt is OD to the distance between (r, s)；vbGone on a journey for regular public traffic
Average speed；
For regular public traffic go on a journey waiting time,F is regular public traffic departure frequency；
It is crowded with detecting period change type for in-car, For
OD amounts of the OD to selection regular public traffic trip mode between (r, s)；sbFor seating capacity in regular public traffic compartment；λ is compartment standing room
Area；α1=0.021；α2=1.82；
For regular public traffic admission fees of the OD to (r, s)；
S2-2 calculates broad sense Trip Costs functions of the OD to the customization bus trip between (r, s)Including travel time and ticket
Valency：
<mrow>
<msubsup>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>d</mi>
</msubsup>
<mo>=</mo>
<mi>&beta;</mi>
<mo>&times;</mo>
<msubsup>
<mi>t</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>d</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>p</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>d</mi>
</msubsup>
</mrow>
1
In formula, β is traveler long-run cost rate,To customize bus trip journey time,lrsIt is OD to (r, s)
The distance between, vdFor customization bus trip average speed；
For in OD to the customization public transport fares on (r, s)；
S2-3 calculates broad sense Trip Costs functions of the OD to (r, s) upper pathway k car tripIncluding travel time, combustion
It is oily to take：
<mrow>
<msubsup>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>=</mo>
<mi>&beta;</mi>
<mo>&times;</mo>
<msubsup>
<mi>t</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>c</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>+</mo>
<mi>g</mi>
<mo>&times;</mo>
<msub>
<mi>l</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
</msub>
</mrow>
In formula, β is traveler long-run cost rate,The trip journey time for being car on the k of path, For the relation variable in section and path, if section a is on the kth paths between (r, s), thenOtherwise,A is the set in all sections；
G is that car unit mileage fuel oil takes；lrs,kFor distances of the OD to the kth paths between (r, s)；
For journey time of the car on a of section, it can be calculated using BPR functions, i.e.,：
<mrow>
<msubsup>
<mi>t</mi>
<mi>a</mi>
<mrow>
<mi>c</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>t</mi>
<mi>a</mi>
<mn>0</mn>
</msubsup>
<mo>&lsqb;</mo>
<mn>1</mn>
<mo>+</mo>
<mn>0.15</mn>
<msup>
<mrow>
<mo>(</mo>
<mfrac>
<msub>
<mi>x</mi>
<mi>a</mi>
</msub>
<msub>
<mi>c</mi>
<mi>a</mi>
</msub>
</mfrac>
<mo>)</mo>
</mrow>
<mn>4</mn>
</msup>
<mo>&rsqb;</mo>
</mrow>
In formula,For section a free flow running time；xaFor section a car transportation amount, For path k car transportation amount；caFor road section capacity；R、S、KrsSet, the set of terminal of starting point are represented respectively
With OD to the set of paths between (r, s)；
OD is calculated to the broad sense Trip Costs of the car trip in all paths between (r, s), takes minimum value as OD to (r, s)
Car trip minimum broad sense Trip Costs：
<mrow>
<msubsup>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>=</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mo>{</mo>
<msubsup>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>}</mo>
<mo>.</mo>
</mrow>
6. customization public transport pricing method according to claim 5, it is characterised in that upper strata plan model is set up in step S3
The step of include：
To realize system optimal as target making admission fee, traffic system under fixed demand is optimal to be equivalent to system synthesis originally most
Small, system synthesis sheet includes operation totle drilling cost and traveler totle drilling cost, and its object function is represented by：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>min</mi>
<mi> </mi>
<mi>Z</mi>
<mo>=</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
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<mo>&Element;</mo>
<mi>R</mi>
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<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>s</mi>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<mi>&beta;</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>t</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>b</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>t</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>b</mi>
<mo>,</mo>
<mi>w</mi>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>t</mi>
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<mi>r</mi>
<mi>s</mi>
</mrow>
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<mi>b</mi>
<mo>,</mo>
<mi>c</mi>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<msubsup>
<mi>q</mi>
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<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>b</mi>
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</mtd>
</mtr>
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<mo>+</mo>
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<mi>&Sigma;</mi>
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<mrow>
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</mrow>
</munder>
<mi>&beta;</mi>
<mo>&times;</mo>
<msubsup>
<mi>t</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>d</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>&times;</mo>
<msubsup>
<mi>q</mi>
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<mi>r</mi>
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<mi>&Sigma;</mi>
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<mi>A</mi>
</mrow>
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<mi>c</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msubsup>
<mo>+</mo>
<mi>g</mi>
<mo>&times;</mo>
<msub>
<mi>l</mi>
<mi>a</mi>
</msub>
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</mrow>
<msub>
<mi>x</mi>
<mi>a</mi>
</msub>
</mrow>
</mtd>
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<mo>+</mo>
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</mrow>
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<msubsup>
<mi>C</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>d</mi>
<mo>,</mo>
<mn>0</mn>
</mrow>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
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<mrow>
<mi>s</mi>
<mo>&Element;</mo>
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</mrow>
</munder>
<msubsup>
<mi>C</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>d</mi>
<mo>,</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mo>&times;</mo>
<msubsup>
<mi>q</mi>
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<mi>r</mi>
<mi>s</mi>
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<mo>&Element;</mo>
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<mrow>
<mi>s</mi>
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</mrow>
</munder>
<msubsup>
<mi>C</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>b</mi>
<mo>,</mo>
<mn>0</mn>
</mrow>
</msubsup>
<mo>+</mo>
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<mi>&Sigma;</mi>
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<mi>r</mi>
<mo>&Element;</mo>
<mi>R</mi>
</mrow>
</munder>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>s</mi>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msubsup>
<mi>C</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mrow>
<mi>b</mi>
<mo>,</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mo>&times;</mo>
<msubsup>
<mi>l</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>b</mi>
</msubsup>
<mo>&times;</mo>
<mi>f</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
In formula, Z represents system synthesis sheet, i.e. traveler totle drilling cost and operation totle drilling cost sum；Represent in OD between (r, s)
The travel amount of selection customization bus trip mode；laRepresent section a length；Consolidating for public transport company is customized to (r, s) for OD
Determine operation cost；The average variable specific discharge operation cost of public transport company is customized to (r, s) for OD；For OD to (r,
S) the fixation operation cost of regular public traffic company；The average variable unit mileage of (r, s) regular public traffic company is runed for OD
Cost；Represent operation mileages of the OD to regular public traffic between (r, s)；F is regular public traffic departure frequency.
7. customization public transport pricing method according to claim 5, it is characterised in that lower floor's plan model is set up in step S3
The step of include：
By assuming：Car trip optimizing paths meet the stochastic user equilibrium criterion based on Logit, and car mode goes out
Row meets stochastic user equilibrium condition, i.e. OD and the car trip amount that path k is selected between (r, s) can be calculated by following formula：
<mrow>
<msubsup>
<mi>q</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>q</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>&times;</mo>
<mfrac>
<mrow>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msubsup>
<mi>&theta;U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>K</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
</msub>
</mrow>
</munder>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msubsup>
<mi>&theta;U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>c</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
</mrow>
In formula,Refer to OD to car trip amount total between (r, s)；
By assuming：Traveler in network can only be arrived at by three kinds of modes, i.e. regular public traffic, customization public transport and small vapour
Car, the three kinds of trip modes corresponded respectively in set M={ b, d, c }, the probability that three kinds of modes are selected obeys Logit model meters
Formula is calculated, Passenger Traveling Choice meets Logit formula, i.e.,：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msubsup>
<mi>&eta;U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>&Element;</mo>
<mi>M</mi>
</mrow>
</munder>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msubsup>
<mi>&eta;U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
</mrow>
<mrow>
<msubsup>
<mi>q</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>=</mo>
<msub>
<mi>Q</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
</msub>
<mo>&times;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
</mrow>
In formula,The probability of m class trip mode is selected (r, s) for OD；The wide of m class trip modes is selected to (r, s) for OD
Adopted Trip Costs；QrsFor the OD OD amounts total to (r, s)；The OD amount of m class trip mode is selected (r, s) for OD；θ reflects
Understanding difference of the passerby to each path disutility；η reflects that traveler is born to regular public traffic, three kinds of modes of customization public transport and car
The understanding difference of effectiveness；
By discrete Choice Theory, OD is to the minimum broad sense Trip Costs of expectation between (r, s)：
<mrow>
<msub>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
</msub>
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<mi>E</mi>
<mo>|</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mo>{</mo>
<msubsup>
<mi>U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>}</mo>
<mo>|</mo>
<mo>=</mo>
<mo>-</mo>
<mfrac>
<mn>1</mn>
<mi>&eta;</mi>
</mfrac>
<mi>l</mi>
<mi>n</mi>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>&Element;</mo>
<mi>M</mi>
</mrow>
</munder>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msubsup>
<mi>&eta;U</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
The analysis described according to network, sets up the mathematical programming model of following multimode Stochastic User Equilibrium of equal value：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>min</mi>
<mi> </mi>
<mi>Z</mi>
<mo>=</mo>
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</mrow>
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<mrow>
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<mi>t</mi>
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<mi>s</mi>
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<mo>&Element;</mo>
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</mrow>
</munder>
<mi>&beta;</mi>
<mo>&times;</mo>
<msubsup>
<mo>&Integral;</mo>
<mn>0</mn>
<msubsup>
<mi>q</mi>
<mrow>
<mi>r</mi>
<mi>s</mi>
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<mi>&beta;</mi>
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<mn>0</mn>
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<mi>x</mi>
<mi>a</mi>
</msub>
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<mi>g</mi>
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<mi>l</mi>
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<msub>
<mi>x</mi>
<mi>a</mi>
</msub>
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</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mfrac>
<mn>1</mn>
<mi>&theta;</mi>
</mfrac>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>r</mi>
<mo>&Element;</mo>
<mi>R</mi>
</mrow>
</munder>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>s</mi>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<munder>
<mi>&Sigma;</mi>
<mrow>
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<mo>&Element;</mo>
<msub>
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<msubsup>
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</msubsup>
<mo>-</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mfrac>
<mn>1</mn>
<mi>&eta;</mi>
</mfrac>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>r</mi>
<mo>&Element;</mo>
<mi>R</mi>
</mrow>
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<munder>
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<mrow>
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<mo>&Element;</mo>
<mi>M</mi>
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</mtd>
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</mtable>
</mfenced>
s.t.
<mrow>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>&Element;</mo>
<mi>M</mi>
</mrow>
</munder>
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<mi>q</mi>
<mrow>
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</mrow>
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</msubsup>
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<msub>
<mi>Q</mi>
<mrow>
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<mi>s</mi>
</mrow>
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<mo>&Sigma;</mo>
<mrow>
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<mo>&Element;</mo>
<msub>
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<mrow>
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</mrow>
</msub>
</mrow>
</munder>
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<mi>q</mi>
<mrow>
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<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
<mrow>
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<mrow>
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</mrow>
xa≤ca
In formula, Z represents system synthesis sheet, i.e. traveler totle drilling cost and operation totle drilling cost sum；
Above-mentioned first be constrained to OD flows model split conservation constraints；Second be constrained to car flow Path selection
Conservation constraints；3rd be constrained to three kinds of mode flows nonnegativity restrictions；4th be constrained to car path flow non-negative
Constraint；5th be constrained to link flow capacity consistency condition.
8. customization public transport pricing method according to claim 1, it is characterised in that strong using global convergence in step S4
Genetic algorithm iterated between upper strata plan model and lower floor's plan model to approach the optimal solution of Bi-level Programming Models,
Wherein, underlying model is solved by sequential quadratic programming algorithm.
9. customization public transport pricing method according to claim 1, it is characterised in that step S4 is comprised the following steps that：
S4-1 is initialized：The encoding scheme of genetic algorithm chromosome is designed, parameter is determined；Random generation customization public transport fares, and
Substitute into lower floor's plan model kind and solve flow, obtain S group chromosomes, constitute initial population P0；
S4-2 object functions are calculated：Upper strata desired value Z is solved to S group chromosomes respectivelys, and record maximum target value and its correspondence
Chromosome；
S4-3 stop technologies：If evolutionary generation gen reaches maximum evolutionary generation maxgen, stop algorithm, decode chromosome,
Export the admission fee and flow in optimal solution；Otherwise step S4-4 is carried out；
S4-4 carries out genetic manipulation：Selection is performed, intersects and makes a variation, and the customization public transport fares after evolution are substituted into lower floor's planning
Model, solves flow, constitutes new population Pgen+1；Return to step S4-2.
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