CN103218670A - Urban railway traffic random passenger flow loading method - Google Patents

Abstract

The invention discloses an urban railway traffic random passenger flow loading method which comprises the following steps: 1.1, initializing, dividing one day into a plurality of time windows averagely, loading basic data, at the same time, setting the total number of the time windows as n, setting and marking an initial value of a variable t of the time windows as 1, and setting an initial value CN1 of road congestion charge as 0; 1.2, reading an origin and destination (OD) distribution volume of a tth time window, based on a basically effective path collection, calculating time of a first regular bus and a last regular bus of each path, judging the relationship of the time and the tth time window, and generating a dynamic effective path collection; 1.3, based on the dynamic effective path collection and an urban railway traffic passenger going-out path selection model, confirming a selected portion of each effective path between the OD, and obtaining a path flow; 1.4, performing statistics on a passenger flow of each section of a road, and updating the road congestion charge CNt+1; and 1.5, stopping the judgment, if the t is less than n, t=t+1 and continuing to iterate from the step 1.2, or, stopping the method.

Description

A kind of urban track traffic is the passenger flow loading method at random

Technical field

The present invention relates to the track traffic technical field, relate in particular to a kind of urban track traffic passenger flow loading method at random.

Background technology

Urban track traffic network passenger flow loading at random is the final link of urban track traffic for passenger flow demand forecast, not only can obtain important passenger flow indexs such as section flow, transfer amount and circuit flow by the passenger flow loading is equipped with and the train operation plan establishment to instruct the train capacity, can also obtain different subject of operations' freight allocating table, so the passenger flow of efficiently and accurately is loaded with important practical sense.

Present urban track traffic network is the passenger flow loading method at random, is divided into based on the theoretical loading of collection meter with based on the loading of non-collection meter theory (Logit or Probit model).Based on the theoretical loading result of the passenger flow at random demonstration of collection meter is the macroscopic statistics rule, analyze the go on a journey microcosmic in path of passenger and select behavior and load the subordinate act Angle of Interpretation based on the passenger flow at random of non-collection meter theory, thus based on the passenger flow at random of non-collection meter theory load more can reflect reality, more accurate.But based on the urban track traffic network passenger flow loading at random of non-collection meter theory, lack of the influence of consideration road network topology structure and path trend at present to passenger's routing; Generally represent Congestion surcharge usefulness, can't reflect the continuous variation of Congestion surcharge, and partial parameters wherein generally derives from empirical value the influence of passenger's routing preference with piecewise function; The general influence of ignoring the restriction of first and last regular bus to the passenger flow loading result.

Summary of the invention

In order to overcome the deficiency of prior art structure, the invention provides a kind of urban track traffic passenger flow loading method at random.

The embodiment of the invention discloses a kind of urban track traffic passenger flow loading method at random, may further comprise the steps:

1.1, initialization, to on average be divided into a plurality of time windows in one day, and load OD abundance under road network topology data, time-table, each time window, the setting-up time window adds up to n simultaneously, the initial value of setting the variable t of mark time window is 1, sets the initial value CN of highway section Congestion surcharge with index ₁=0;

1.2, read the OD abundance of t time window, based on basic active path set, calculate the first and last regular bus time in each path, judge the relation of this time and t time window, generate dynamic active path and gather RSET _t

1.3, based on dynamic active path set RSET _tWith the urban track traffic passenger path Choice Model of going on a journey, determine each active path selection percentage between OD, obtain the path flow, wherein, urban track traffic passenger urban track traffic passenger that the utility function of path Choice Model set up when basic active path set makes up in the step 1.2 routing utility function of going on a journey of going on a journey;

1.4, the volume of the flow of passengers of adding up each highway section, upgrade highway section Congestion surcharge CN _T+1

1.5, stop to judge that if t＜n, then t=t+1 continues iteration from step 1.2; Otherwise this method stops.

Further, as preferably, the structure of basic active path set may further comprise the steps in the described step 1.2:

2.1, make up the urban track traffic passenger routing utility function of going on a journey, variable in the utility function walks line time, number of transfer and crowded cost element except admission fee, turnover station time, riding time, platform Waiting time, transfer, also introduced the angle expense and expressed the influence to passenger's routing of road network topology and path trend;

2.2, based on the equivalence riding time coefficient, other factors are converted into riding time one after another;

2.3, determine the tolerance threshold value of passenger to the time;

2.4, utilize the Double-sweep searching algorithm to determine the set of basic active path.

The present invention carries out having added when passenger flow loads first and last regular bus time restriction condition, and kernel model has been introduced the angle expense and has been expressed the influence to the passenger routing of road network structure and path trend, Congestion surcharge is treated to the product of compartment load factor and highway section working time, with of the continuous variation of same function reflection Congestion surcharge, loading rationality and path flow estimation precision have been improved to the influence of passenger's routing preference.

Description of drawings

When considered in conjunction with the accompanying drawings, by the reference following detailed, can more completely understand the present invention better and learn wherein many attendant advantages easily, but accompanying drawing described herein is used to provide further understanding of the present invention, constitute a part of the present invention, illustrative examples of the present invention and explanation thereof are used to explain the present invention, do not constitute to improper qualification of the present invention, wherein:

Fig. 1 is an embodiment of the invention urban track traffic passenger flow loading method process flow diagram at random.

Fig. 2 is an angle expense exemplary plot.

Embodiment

With reference to Fig. 1-2 embodiments of the invention are described.

For above-mentioned purpose, feature and advantage can be become apparent more, the present invention is further detailed explanation below in conjunction with the drawings and specific embodiments.

As shown in Figure 1, a kind of urban track traffic is the passenger flow loading method at random, and the embodiment of this method is as follows.

S1, initialization:

(1) on average be divided into each time window with one day, the 1st time window is the zero-time section of every day, and the initial value of setting the variable t of mark time window is 1, and time window adds up to n.

(2) load under road network topology data, time-table, each time window basic data such as OD abundance.

(3) the Congestion surcharge initial value used in highway section is 0, i.e. CN ₁=0.

S2, read the t time window the OD(starting point to terminal) abundance, based on basic active path set, calculate the first and last regular bus time in each path, judge the relation of this time and t time window, generate dynamic active path and gather RSET _t(the active path set of t time window).

Dynamically active path is gathered RSET _tThe generation method, be under the t time window following processing to be done in each path in the set of basic active path: the first vehicle hour puts aside greater than this time window or the final vehicle hour path less than this time window; The path that first vehicle hour is between this time window is considered by normal current path; The path that final vehicle hour is between this time window is that node is refined as little time window with the final vehicle hour, and determines OD abundance under the little time window according to the proportion of the shared time window of little time window, and normal current path is can be regarded as in this path under this little time window.

S3, based on RSET _tWith the urban track traffic passenger path Choice Model (time window is in morning peak, evening peak or flat peak phase, model parameter difference) of going on a journey, determine each active path selection percentage between OD, obtain the path flow.

${\mathrm{ql}}_k^{\mathrm{rs}}=\frac{\exp \left(V_k^{\mathrm{rs}}\right)}{\mathrm{\Σexp}\left(V_k^{\mathrm{rs}}\right)}\×q_{\mathrm{rs}}---\left(1\right)$

In the formula,

Be the volume of the flow of passengers of k bar active path between the OD from r to s (unit: person-time); q _RsBe the timesharing OD abundance from r to s (unit: person-time);

Be the routing effectiveness of k bar active path between the OD from r to s, the urban track traffic passenger who is set up during by the set of the basic active path among the S2 structure routing utility function of going on a journey is determined.

S4, S6, the volume of the flow of passengers of adding up each highway section are upgraded the highway section Congestion surcharge and are used.

CN _t+1=qplink*TRlink (2)

Wherein, CN _T+1The highway section Congestion surcharge usefulness of upgrading when being the t time iteration (unit: hour); Qplink is the highway section load factor; TRlink is the working time (unit: hour) in highway section.

S5, termination are judged.If t＜n, then t=t+1 continues iteration from S2; Otherwise this method stops.

Wherein, the building process of basic active path set is as follows among the above-mentioned S2

(1) makes up the urban track traffic passenger routing utility function of going on a journey.

Based on MNL (Multinomial Logit) model, made up the urban track traffic passenger routing utility function of going on a journey, this function has not only been considered admission fee, turnover station time, riding time, platform Waiting time, has been changed to factors such as line time, number of transfer and Congestion surcharge, also introduced the angle expense and expressed the influence of road network topology and path trend, simultaneously Congestion surcharge has been treated to the product of compartment load factor and respective stretch working time passenger's routing.

$V_k^{\mathrm{rs}}=-{\mathrm{\Σ}}_{i=1}^m{\mathrm{\β}}_i{X}_{\mathrm{ik}}^{\mathrm{rs}}---\left(3\right)$

In the formula, Routing effectiveness for k paths between the OD from r to s;

I characteristic attribute value (comprise admission fee, turnover station time, riding time, platform Waiting time, change to line time, number of transfer, Congestion surcharge usefulness and angle expense factors such as (path trends)) for k paths between the OD from r to s; β _iParameter for the individual features attribute; M is the influence factor number.

Wherein, the angle expense, as Fig. 2, be that passenger's each highway section, path trend of going on a journey is departed from from the punishment of the through direction of origin-to-destination, this value should increase progressively with the increase of deviation angle and road section length, and variation tendency is also with the increasing progressively and increase of deviation angle, and promptly the angle cost function is that single order can be led, and derived function is the increasing function greater than 0, is expressed as follows:

${\mathrm{AC}}_k^{\mathrm{rs}}=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{L}_i*\tan ({\mathrm{\θ}}_i/4)---\left(4\right)$

In the formula:

Angle expense for k paths between the OD from r to s; L _iLength for the i highway section of this paths; θ _iFor departing from from the angle of the through direction of origin-to-destination in the i highway section of this paths, value is [0, π]; M is the highway section number of this paths.

This function has been considered admission fee, turnover station time, riding time, platform Waiting time, has been changed to line time, number of transfer, Congestion surcharge usefulness and angle expense factors such as (path trends).Especially the introducing of angle expense has been corrected all the time road network topology and path trend to the ignorance of the influence of passenger routing.

A. admission fee.Urban track traffic is chargeed dual mode, and the one, " flat fare "; Another kind is by traveling mileage block meter rate, thereby admission fee p is expressed as p=δ * p'.In the formula, δ is the sign amount, is 0 when " flat fare ", is 1 during the segmentation valuation; P' is the admission fee constant when " flat fare ", is the admission fee piecewise function during segmentation valuation.

B. pass in and out the station time, mainly comprise from swiping the card and entering the station the time of entering the station of platform and departures time, represent with IOt from platform to the departures of swiping the card.

C. riding time, mainly be included between the working time and station stopping time in the compartment, represent with IVt.

D. the platform Waiting time refers on platform and waits for the time that vehicle arrives, and represents with Wt.Waiting time mainly is subjected to the departure interval influence of (TSt) and compartment load factor (qplink) between the stopping time at the station of this platform of (Int), this car, the arrival obedience of supposing the passenger evenly distributes, and the passenger arrives at twice o'clock at vehicle and always once can get on the bus, and then the platform Waiting time is: Wt=(Int+TSt)/2+ δ ' * Int.Wherein, as qplink〉120% the time, δ ' gets 1, otherwise gets 0.

E. line time is walked in transfer, refers to the line time of walking from a train to another train, represents with Trt.

F. number of transfer is represented with Trs.

G. Congestion surcharge usefulness is represented path Congestion surcharge usefulness with VP.

$\mathrm{VP}=\frac{{\mathrm{\Σ}}_{u=1}^l({\mathrm{CN}}_{u,i1}*{\mathrm{\δ}}_{k,u}^{\mathrm{rs}})}{{\mathrm{\Σ}}_{u=1}^l\left({\mathrm{\δ}}_{k,u}^{\mathrm{rs}}\right)}---\left(5\right)$

Wherein, VP uses for the path Congestion surcharge; CN _{U, i-1}The highway section Congestion surcharge usefulness of the highway section u that upgrades when being the i-1 time iteration (unit: hour); If highway section u is on k paths between the OD from r to s, Be 1, otherwise be 0.

H. angle expense (Angular Cost) is represented with AC, utilizes formula (3) to try to achieve.

The passenger utilizes the maximum likelihood estimation technique, t value method of inspection and goodness of fit criterion to carry out parameter calibration in morning peak, the trip routing preference difference of evening peak peace peak phase, and the result is as follows:

${\mathrm{MV}}_k^{\mathrm{rs}}=-0.12I{\mathrm{Ot}}_k^{\mathrm{rs}}-2.9{\mathrm{IVt}}_k^{\mathrm{rs}}-0.21{\mathrm{Wt}}_k^{\mathrm{rs}}-0.24{\mathrm{Trt}}_k^{\mathrm{rs}}-3.2{\mathrm{Trs}}_k^{\mathrm{rs}}-5.8{\mathrm{VP}}_k^{\mathrm{rs}}-4.03{\mathrm{AC}}_k^{\mathrm{rs}}---\left(6\right)$

${\mathrm{EV}}_k^{\mathrm{rs}}=-2.2I{\mathrm{Ot}}_k^{\mathrm{rs}}-3.9{\mathrm{IVt}}_k^{\mathrm{rs}}-1.36{\mathrm{Wt}}_k^{\mathrm{rs}}-0.58{\mathrm{Trt}}_k^{\mathrm{rs}}-4.8{\mathrm{Trs}}_k^{\mathrm{rs}}-7.22{\mathrm{VP}}_k^{\mathrm{rs}}-5.1{\mathrm{AC}}_k^{\mathrm{rs}}---\left(7\right)$

${\mathrm{CV}}_k^{\mathrm{rs}}=-0.19{\mathrm{IOt}}_k^{\mathrm{rs}}-2.91{\mathrm{IVt}}_k^{\mathrm{rs}}-0.1{\mathrm{Wt}}_k^{\mathrm{rs}}-0.52{\mathrm{Trt}}_k^{\mathrm{rs}}-3.9{\mathrm{Trs}}_k^{\mathrm{rs}}-54.7{\mathrm{VP}}_k^{\mathrm{rs}}-3.03{\mathrm{AC}}_k^{\mathrm{rs}}---\left(8\right)$

In the formula:

The routing effectiveness of k paths between the OD during for morning peak from r to s;

The routing effectiveness of k paths between the OD during for evening peak from r to s;

The routing effectiveness of k paths between the OD during for flat peak from r to s.Because of the present invention, so do not have the admission fee factor, i.e. δ=0 data from " a ticket system " urban track traffic network.

(2) equivalent time transforms, and based on formula (4) (5) (6), utilizes formula (8) respectively, can obtain the equivalent riding time of morning peak, evening peak peace each factor of peak phase.

ETTC _i＝β _i/β ₁ (9)

In the formula, ETTC _iIt is equivalent riding time coefficient of i attribute; β _iBe the coefficient of i attribute in model; β ₁Be the coefficient of riding time in model.

(3) passenger analyzes the time degrees of tolerance, and the passenger comprises absolute tolerance and relative tolerance to the time to the tolerance of time, as formula (8)

T _i≤min(tt+H，C*t) (10)

In the formula, T _iFor OD to T.T. of certain paths; Tt be OD to T.T. of shortest path; H is an absolute threshold; C is a relative ratio.Advised C=2.7 H=13.39 minute.

(4) utilize the Double-sweep algorithm, filter out each OD to K bar shortest path, and then by the passenger to the restriction of the degrees of tolerance of time, the path that deletion does not satisfy condition constructs basic active path set.

Though more than described the specific embodiment of the present invention, but those skilled in the art is to be understood that, these embodiments only illustrate, those skilled in the art can carry out various omissions, replacement and change to the details of said method and system under the situation that does not break away from principle of the present invention and essence.For example, merge the said method step, then belong to scope of the present invention to realize the identical result of essence thereby carry out the essence identical functions according to the identical method of essence.Therefore, scope of the present invention is only limited by appended claims.

Claims (2)

1. urban track traffic passenger flow loading method at random is characterized in that, may further comprise the steps:

1.1, initialization, to on average be divided into a plurality of time windows in one day, and load OD abundance under road network topology data, time-table, each time window, the setting-up time window adds up to n simultaneously, the initial value of setting the variable t of mark time window is 1, sets the initial value CN that the highway section Congestion surcharge is used ₁=0;

1.2, read the OD abundance of t time window, based on basic active path set, calculate the first and last regular bus time in each path, judge the relation of this time and t time window, generate dynamic active path and gather RSET _t

1.3, based on dynamic active path set RSET _tWith the urban track traffic passenger path Choice Model of going on a journey, determine each active path selection percentage between OD, obtain the path flow, wherein, urban track traffic passenger urban track traffic passenger that the utility function of path Choice Model set up when basic active path set makes up in the step 1.2 routing utility function of going on a journey of going on a journey;

1.4, the volume of the flow of passengers of adding up each highway section, upgrade highway section Congestion surcharge CN _T+1

1.5, stop to judge that if t＜n, then t=t+1 continues iteration from step 1.2; Otherwise this method stops.

2. according to the described urban track traffic of claim 1 passenger flow loading method at random, it is characterized in that the structure of basic active path set may further comprise the steps in the described step 1.2:

2.1, make up the urban track traffic passenger routing utility function of going on a journey, variable in the utility function walks line time, number of transfer and crowded cost element except admission fee, turnover station time, riding time, platform Waiting time, transfer, also introduced the angle expense and expressed the influence to passenger's routing of road network topology and path trend;

2.2, based on the equivalence riding time coefficient, other factors are converted into riding time one after another;

2.3, determine the tolerance threshold value of passenger to the time;

2.4, utilize the Double-sweep searching algorithm to determine the set of basic active path.

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