CN101441680A - Method for improving high speed rail train operation right time rate by running chart robustness - Google Patents

Abstract

The invention discloses a method for improving the on-schedule rate of the operation of a high-speed railway train by utilizing the robustness of a working diagram in the technical field of operation dispatching and control of high-speed trains. The method adopts a technical proposal that a preset working diagram is subject to formal representation; a polynomial matrix expression form of the working diagram is given to evaluate a feature value; then the perturbation of the working diagram is defined, and the ratio of the perturbation and the total delay time is utilized to weigh the robustness of the working diagram; a Petri network is utilized to simulate the operation of the train in a section, and the deviation of the arrival and departure time of the train and diagram-specified time produced during the simulation is fed back to the perturbation calculation; the robustness of the working diagram is calculated; according to the requirement of the robustness of the preset working diagram, the arrival and departure time of the train in the working diagram is adjusted, and then the operation simulation of the train and the robustness calculation are performed; and the circulation is performed until the robustness of the working diagram achieves the preset requirement. The method provides an evidence for establishing high-efficiency railway working diagrams and assuring the safe, punctual and high-speed operation of railways.

Description

Utilize the service chart robustness to improve the method for high speed rail train operation percent of punctuality

Technical field

The invention belongs to bullet train traffic control control technology field, relate in particular to a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality.

Background technology

Along with coming into operation of high-speed railway, the establishment of the service chart of bullet train more and more comes into one's own.The establishment of service chart is to making full use of capacity of through train traffic, satisfying passenger's transmission demand and have decisive meaning.Outstanding railway operation figure can be according to the driveability of railroad train reality, bring into play the transportation effect of railroad train to greatest extent, guarantee train as much as possible according to set the setting out and operation time of arrival of service chart, promptly the percent of punctuality of train actual travel is high as much as possible.On the contrary, it is improper that railway operation figure works out, and is difficult to guarantee railroad train according to set the setting out and the due in operation of service chart, and promptly late rate increases, and final result can not effectively bring into play the actual effect of railroad train transportation.

The quality of railway operation figure is to weigh by the robustness of service chart.For high-speed railway, service chart has intensive, periodic characteristics, the computational analysis method of existing line service chart robustness was difficult to adapt to the research of high-speed railway service chart in the past, so, press for the robustness of high-speed railway service chart is studied, so that cook up high-speed railway service chart efficiently by it.At present, research to the robustness of high-speed railway service chart still is in the elementary step, the present invention proposes index and computing method that high-speed railway service chart robustness is weighed, and the method that improves high-speed railway operation percent of punctuality by high-speed railway service chart robustness is provided.

Summary of the invention

Index and computing method that high-speed railway service chart robustness is weighed have been the objective of the invention is to propose, and the method that improves high-speed railway operation percent of punctuality by high-speed railway service chart robustness is provided, solve the problem that the formulation of present high-speed railway service chart is theoretically unsound.

Technical scheme of the present invention is, a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality, and described method comprises the following steps:

Step 1: carry out formalization representation to setting railway operation figure;

Step 2: the numerical value that requires of setting the service chart robustness;

Step 3: provide the polynomial matrix expression-form of railway operation figure, generate the set service chart matrix GD constantly that sets out ⁰

Step 4: utilize the Petri net that train operating conditions in the section is simulated, make it satisfy restrictive condition in the train operation; The operation actual achievement that the generates train matrix GD constantly that sets out; Calculate total late time;

Step 5: the actual achievement train arrival ﹠ leaving that will produce in will simulating feeds back in the calculating of perturbation amount with set service chart deviation constantly constantly, calculates the perturbation matrix $\tilde{T}=\mathrm{GD}-{\mathrm{GD}}^0;$

Step 6: make λ and Be respectively actual achievement due in matrix GA and

Eigenwert on maximum algebra, then the perturbation amount that is caused by the parameter perturbation is defined as: $\mathrm{\ρ}\left(\mathrm{\λ}\right)=|\widetilde{\mathrm{\λ}}-\mathrm{\λ}|,$ Obtain eigenwert ρ (λ);

Step 7: the robustness of calculating service chart;

Step 8: judge that whether the service chart robustness is less than the numerical value of setting that requires;

Step 9: if, then revise railway operation figure, jump to step 1, repeat above-mentioned steps more than or equal to the numerical value of setting that requires;

Step 10: if less than the numerical value of setting that requires, the service chart of step 1 is satisfactory high-speed railway service chart.

The described Petri of utilization net is simulated train operating conditions in the section, be with the interval in the section and station storehouse institute as the Petri net, train be moved enter from a storehouse another storehouse as the transition of Petri net, train is as the Tuo Ken of Petri net.

Described total late time is meant that all trains arrive the summation of late time at last station of this section.

The robustness of described calculating service chart obtains divided by total late time by ρ (λ).

The invention provides a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality.For working out railway operation figure efficiently, guarantee that railway security, punctual, high-speed cruising provide foundation.

Description of drawings

Fig. 1 utilizes the service chart robustness to improve the method flow diagram of high speed rail train operation percent of punctuality.

Fig. 2 utilizes the Petri net to train operating conditions simulation drawing in the section.Among Fig. 2, storehouse institute 201, the train holder agree 202, and idle holder agree 203, transition 204.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that following explanation only is exemplary, rather than in order to limit the scope of the invention and to use.

Fig. 1 utilizes the service chart robustness to improve the method flow diagram of high speed rail train operation percent of punctuality.Among Fig. 1, step 101: at first carry out formalization representation to setting railway operation figure.If total N train in the section of research, M station.Here quote the notion of car plan, so-called car plan just be meant certain train in section each station from initial station to whole station to sending out a time and an operation property.Then train i AT STATION the plan of k be a tlv triple.Can be described as: P _Ik={ a _Ik, pr _Ik, d _Ik, i=1,2 ..., N, k=1,2 ..., M, wherein a _Ik, d _IkBe respectively the time of arrival and the time of departure of train i.So, actual operating state can be by each train through the characterizing to a time of each station, thereby can be described by the plan of N * M point, promptly

$\mathrm{OG}=\left|\begin{array}{cccc}{P}_{11}& P_{12}& \·\·\·& P_{1M}\\ P_{21}& P_{22}& \·\·\·& P_{2M}\\ \·\·\·& \·\·\·& P_{\mathrm{ik}}& \·\·\·\\ P_{N1}& P_{N2}& \·\·\·& P_{\mathrm{NM}}\end{array}\right|$

Because P _IkBe a tlv triple, so OG can be decomposed into arrival matrix GA, matrix GD and working signal matrix PR set out:

$\mathrm{GA}={\left\{a_{\mathrm{ik}}\right\}}_{N\×M}=\left|\begin{array}{cccc}{a}_{11}& a_{12}& \·\·\·& a_{1M}\\ a_{21}& a_{22}& \·\·\·& a_{2M}\\ \·\·\·& \·\·\·& a_{\mathrm{ik}}& \·\·\·\\ a_{N1}& a_{N2}& \·\·\·& a_{\mathrm{NM}}\end{array}\right|$

$\mathrm{GD}={\left\{d_{\mathrm{ik}}\right\}}_{N\×M}=\left|\begin{array}{cccc}{d}_{11}& d_{12}& \·\·\·& d_{1M}\\ d_{21}& d_{22}& \·\·\·& d_{2M}\\ \·\·\·& \·\·\·& a_{\mathrm{ik}}& \·\·\·\\ d_{N1}& d_{N2}& \·\·\·& d_{\mathrm{NM}}\end{array}\right|$

For planned train graph, its each relevant matrix is respectively: plan arrives matrix: ${\mathrm{GA}}^P={\left\{a_{\mathrm{ik}}^P\right\}}_{N\×M}$ With the plan matrix that sets out: ${\mathrm{GD}}^P={\left\{d_{\mathrm{ik}}^P\right\}}_{N\×M}.$

Step 102: set the numerical value that requires of service chart robustness, this example is made as 1.

Step 103: provide the polynomial matrix expression-form of railway operation figure, generate the set service chart matrix GD constantly that sets out ⁰

Train i in the k actual moment of setting out of station is: $d_{\mathrm{ik}}=\max (a_{\mathrm{ik}}+y_{\mathrm{ik}}^{\min },d_{\mathrm{ik}}^0)=a_{\mathrm{ik}}\⊗y_{\mathrm{ik}}^{\min }\⊕d_{\mathrm{ik}}^0;$ The moment at the actual arrival of train i k station is: $a_{\mathrm{ik}}=a_{\mathrm{ik}}^0+{\tilde{t}}_{\mathrm{ik}}.$ Then have $\mathrm{GD}={\{a_{\mathrm{ik}}\⊗y_{\mathrm{ik}}^{\min }\⊕d_{\mathrm{ik}}^0\}}_{N\×M},$ $\mathrm{GA}={\{a_{\mathrm{ik}}\⊗{\tilde{t}}_{\mathrm{ik}}\}}_{N\×M}.$

By top described, generate the set service chart matrix GD constantly that sets out ⁰ ${\mathrm{GD}}^0={\left\{d_{\mathrm{ik}}^0\right\}}_{N\×M}.$

Step 104: utilize the Petri net that train operating conditions in the section is simulated, make it satisfy restrictive condition in the train operation; The operation actual achievement that the generates train matrix GD constantly that sets out; Calculate total late time.

Set up in the process at the Petri net, with the interval in the section and the station storehouse institute as the Petri net, train is moved and enters the transition that another storehouse institute nets as Petri, the Tuo Ken that train is netted as Petri from a storehouse.Along with the propelling of time, simulate the situation of all trains in this section operation, satisfy the various restrictive conditions in the train operation.

Here it is pointed out that section refers to one section circuit between two big stations on the rail track, comprise some stations, and the some intervals between the station.So the interval is the part of section, section comprises the interval, also comprises some stations.Fig. 2 utilizes the Petri net to train operating conditions simulation drawing in the section.Among Fig. 2, storehouse institute 201 represents interval or train in the service chart; The train holder agree 202, the train at expression occupied section or station; Idle holder agree 203, represents interval or station not to have train occupation; On behalf of train, transition 204 enter mobile that another storehouse takes place from a storehouse.The interval is a kind of resource, and the station also is a kind of resource.They all are the resources that can hold train, thereby can represent with the storehouse.Train also is a kind of resource, and it is motion in interval, can agree represent with holder.The model of train is exactly that a holder is agree, and when from a storehouse institute during to another storehouse institute, just to another interval, what entered is interval occupied, the section cleared that is left from an interval in expression.The interval can be described with the storehouse, train holder that this storehouse should comprise is agree or two kinds of resources are agree in the section cleared holder, these two kinds of resources be can not coexist as a storehouse in, promptly an interval can not be not only occupied but also idle, this also can become interval two states, i.e. seizure condition or idle condition.

Train from a storehouse to another storehouse moving process, represent with transition.In computation process, utilize the clock propelling method, whether the condition that each transition of cycle criterion take place is met, if satisfy, transition take place so, the train holder agree disappear in a storehouse, occurs in another storehouse institute.When transition (train arrives to set out at certain station in certain station, train, train move to another interval by an interval) take place, then the attribute of some storehouse institute (arriving the interval at last preceding interval of certain station, station, the previous place of train) should be revised as the free time, and the attribute of some storehouse institute (interval that first interval of station, the back train operation of setting out, train arrive) should be revised as and take.

So circulation is until all this sections of train process.In simulation process, satisfy the various restrictive conditions of train operation, actual is exactly the condition that transition take place.When driving, restrictive condition is the time constraint, and is as follows:

d _ik-a _ik≥Pr _ik×to _ik i＝1，2，...，N k＝1，2，...，M (1)

a _i+1k>d _ik i＝1，2，...，N-1 k＝1，2，...，M (2)

(d _i+1k-d _ik) ²-I ²≥0 i＝1，2，...，N-1 k＝1，2，...，M (3)

d _ik>a _ik i＝1，2，...，N k＝1，2，...，M (4)

d _ik-f ⁱ≥0 i＝1，2，...，N k＝1，2，...，M (5)

a _ik-h ⁱ≥0 i＝1，2，...，N k＝1，2，...，M (6)

Sll _k-N (a _Ik+ t _Stop≤ d _Ik) 〉=0 (7)

a _I+1k-a _Ikτ _{Be dealt into}I=1,2 ..., N-1 k=1,2 ..., M (8)

d _I+1k-d _Ikτ _{To sending out}I=1,2 ..., N-1 k=1,2 ..., M (9)

Formula (1) expression train i must be more than or equal to the required time of technical operation in the down time of station k;

The finish time that is later than the same interval of train occupation that moves ahead the zero hour of formula (2) expression following train occupied section;

The interval sequence constraint of formula (3) train operation shows that train must be in chronological order successively by each interval, and I is a time interval between trains spaced by automatic block signals;

The same train of formula (4) expression begins to take the zero hour of hair line early than the finish time;

Formula (5) represents that the frequency of all trains is later than the time of departure the earliest;

Formula (6) represents that the interval start time of all train occupations is later than turn-on time the earliest;

Formula (7) retrains to the hair line ability for the station, and promptly certain train number of this direction and train sum can not surpass corresponding station circuit number; N (a in the formula _Ik+ t _Stop≤ d _Ik) got to the station k but do not leave the train number of station k of expression;

Formula (8) (9) can not be handled the station of the equidirectional train of sending and receiving simultaneously, and two workshops are not dealt into τ interval time simultaneously every satisfying _{Be dealt into}Do not arrive simultaneously and send out τ interval time _{To sending out}

Utilize the Petri net, by simulation to train operating conditions in the section, the operation actual achievement that obtains all trains matrix GD constantly that sets out.

Calculate total late time, total late time refers to that all trains arrive the summation of late time at last station of this section.

Step 105: the deviation that the train arrival ﹠ leaving of the generation moment and figure regularly carve in will simulating feeds back in the calculating of perturbation amount, calculating perturbation matrix $\tilde{T}=\mathrm{GD}-{\mathrm{GD}}^0.$ Matrix GD changes according to situation about simulating because the operation actual achievement of train is set out constantly, so, and the perturbation matrix $\tilde{T}={\left\{{\tilde{t}}_{\mathrm{ik}}\right\}}_{N\×M}=\mathrm{GD}-{\mathrm{GD}}^0$ Also can change.

Step 106: ask eigenwert $\mathrm{\ρ}\left(\mathrm{\λ}\right)=|\widetilde{\mathrm{\λ}}-\mathrm{\λ}|.$ Wherein, make λ and

Be respectively GA and

Eigenwert on maximum algebra.

Step 107: the robustness value of calculating service chart.Ask eigenwert $\mathrm{\ρ}\left(\mathrm{\λ}\right)=|\widetilde{\mathrm{\λ}}-\mathrm{\λ}|$ After, the robustness of calculating service chart, the i.e. value that obtains divided by total late time by ρ (λ).

From the above, perturbation amount ρ (λ) is big more, illustrates that the interference that train is subjected in operational process is big more, and correspondingly, total late time also can be many more.But,, illustrate that the robustness of set service chart is strong more if total late time is less.Weigh the robustness of service chart so measure ρ (λ) with perturbation divided by total late time, the perturbation amount is certain, and total late time is more little, and the robustness value is big more, and the robustness of service chart is strong more; Otherwise the perturbation amount is certain, and total late time is big more, and the robustness value is more little, and the robustness of service chart is also weak more.The robustness of service chart is to weigh the key index of service chart quality, is the major criterion of weighing transportation organization work quality.

Step 108: judge that whether the service chart robustness requires numerical value 1 less than what set.

Step 109: if require numerical value 1, then revise railway operation figure, jump to step 101, repeat above-mentioned steps more than or equal to what set.

Carrying out railway operation figure when revising, adopting the computation rule in the particle cluster algorithm, providing train arrival ﹠ leaving adjustment amount constantly, adjustment amount is being joined setting out and arriving in the matrix of train.

In order to optimize the robustness of service chart, to constantly adjusting to sending out of service chart, adjustment amount is by the computation rule decision of particle cluster algorithm.Two formula of face as follows, first is to calculate adjustment amount, second is calculated adjusted to sending out constantly.

v _i+1＝ωv _i+c ₁r ₁(p _i-d _i)+c ₂r ₂(p _g-d _i)

d _i+1＝d _i+v _i+1

The moment of setting out with the adjustment train is an example, in the formula, and v _I+1Be that next step is to the adjustment amount constantly that sets out, d _iBe to set out constantly p in the current service chart _iBe the optimum that searches out of present current particle set out constantly p _gBe that the optimum that present all particles search out sets out constantly.c ₁, c ₂Be the non-negative study factor, r ₁, r ₂Be two random numbers between [0,1], ω is an inertial factor, it has kept the inertia of particle movement, makes its trend with expanded search space, the new zone of search of having the ability, by adjusting ω, can keep the balance of algorithm to the overall situation and local search ability.d _I+1Be to adjust new the setting out constantly in back, it is constantly to add that the optimum adjustment amount that population is found out obtains by original setting out.

Utilize this to set out and constantly go to calculate the robustness of new service chart again.Certainly, this just adjusts the element that service chart sets out in the matrix, and each step will be adjusted each element in the matrix that sets out during actual computation.And then carry out robustness and calculate.

Step 110: if reach setting require numerical value 1, the service chart of step 101 is satisfactory high-speed railway service chart.

Here, step 101-step 110 illustrates with following example.6 trains that are located at a section move in 10 intervals, and train is as shown in table 1 at the given time of section operation.S _i(i=1,2 ..., 10) i interval of expression.Train _j(j=1,2 ..., 6) expression j train.The numerical value that requires of setting service chart robustness value is 1.

Each train figure decides working time in the table 1 setting route map of train

	S 1	S 2	S 3	S 4	S 5	S 6	S 7	S 8	S 9	S 10	Sum
												Train 1	18.0	20.0	16.0	220	18.0	100	14.0	10.0	180	15.0	161.0

Train 2	25.0	30.0	20.0	35.0	27.0	15.0	22.0	12.0	24.0	21.0	231.0
												Train 3	18.0	20.0	16.0	22.0	18.0	10.0	14.0	10.0	18.0	15.0	161.0
Train 4	25.0	30.0	20.0	35.0	27.0	15.0	22.0	12.0	24.0	21.0	231.0
												Train 5	18.0	20.0	16.0	22.0	18.0	10.0	14.0	10.0	18.0	15.0	161.0
Train 6	25.0	30.0	20.0	35.0	27.0	15.0	22.0	12.0	24.0	21.0	231.0

Through calculating, the robustness initial value of set service chart is: 3.3601.

The robustness of service chart requires numerical value 1 more than or equal to what set.The robustness value is big more herein, and robustness is poor more, and the late rate of train is high more.So in order to improve the percent of punctuality of bullet train, must adjust train, thereby improve the percent of punctuality of train in the time-division of section operation.According to above-mentioned steps, the utilization particle cluster algorithm is adjusted in the working time of each section each given in service chart train, recomputates the robustness of service chart with this.

The design population scale be 20, then iterating after 56 times, in the service chart each train each interval working time adjusted value as shown in table 2.

Table 2 recomputate the back route map of train in each train figure decide matrix working time

	S 1	S 2	S 3	S 4	S 5	S 6	S 7	S 8	S 9	S 10	Sum
												Train 1	15.0	20.5	14.0	21.0	17.5	8.5	11.0	7.0	14.5	10.0	139.0
Train 2	24.0	29.5	24.5	33.5	23.0	10.5	20.0	10.5	21.0	19.5	216.0
												Train 3	15.5	21.0	13.0	21.5	19.0	8.0	13.0	6.0	13.0	9.0	139.0
Train 4	25.0	32.0	20.5	30.5	23.5	10.5	20.5	10.5	21.0	19.5	214.0
												Train 5	15.5	20.0	13.0	22.0	17.5	8.0	11.0	6.5	15.0	9.5	138.0
Train 6	24.5	33.5	21.3	39.5	23.0	10.5	20.0	10.5	21.0	19.0	223.0

Calculate the adjusted service chart robustness of gained value be this moment: 0.8534, require numerical value less than what the robustness of service chart was set.This explanation adjustment scheme makes service chart that stronger robustness be arranged, and reached set service chart robustness numerical value requirement, and every train is through this section the time, and all there is reduction in various degree the T.T. of operation, makes that the train operation organization scheme is more reasonable.Both save the time, improved the robustness of service chart again.After the robustness of service chart is optimized, also just corresponding raising of train percent of punctuality when operation.

The above; only for the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.

Claims (4)

1, a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality, described method comprises the following steps:

Step 1: carry out formalization representation to setting railway operation figure;

Step 2: the numerical value that requires of setting the service chart robustness;

Step 3: provide the polynomial matrix expression-form of railway operation figure, generate the set service chart matrix GD constantly that sets out ⁰

Step 4: utilize the Petri net that train operating conditions in the section is simulated, make it satisfy restrictive condition in the train operation; The operation actual achievement that the generates train matrix GD constantly that sets out; Calculate total late time;

Step 5: the actual achievement train arrival ﹠ leaving that will produce in will simulating feeds back in the calculating of perturbation amount with set service chart deviation constantly constantly, calculates the perturbation matrix $\tilde{T}=\mathrm{GD}-{\mathrm{GD}}^0;$

Step 6: make λ and

Be respectively actual achievement due in matrix GA and

Eigenwert on maximum algebra, then the perturbation amount that is caused by the parameter perturbation is defined as: $\mathrm{\ρ}\left(\mathrm{\λ}\right)=|\widetilde{\mathrm{\λ}}-\mathrm{\λ}|,$ Obtain eigenwert ρ (λ);

Step 7: the robustness of calculating service chart;

Step 8: judge that whether the service chart robustness is less than the numerical value of setting that requires;

Step 9: if, then revise railway operation figure, jump to step 1, repeat above-mentioned steps more than or equal to the numerical value of setting that requires;

Step 10: if less than the numerical value of setting that requires, the service chart of step 1 is satisfactory high-speed railway service chart.

2, a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality according to claim 1, it is characterized in that the described Petri of utilization net simulates train operating conditions in the section, be with the interval in the section and station storehouse institute as the Petri net, train be moved enter from a storehouse another storehouse as the transition of Petri net, train is as the Tuo Ken of Petri net.

3, a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality according to claim 1 is characterized in that described total late time is meant that all trains arrive the summation of late time at last station of this section.

4, a kind of method of utilizing the service chart robustness to improve the high speed rail train operation percent of punctuality according to claim 1 is characterized in that obtaining the robustness of described calculating service chart divided by total late time by ρ (λ).

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