CN103116608A - Method of reproducing traffic flow on express way - Google Patents

Abstract

The invention relates to a method of reproducing traffic flow on an express way. The method of reproducing traffic flow on the express way is characterized by comprising the steps of a. obtaining traffic data of a simulated road section over a period of time, b. establishing a model according to the traffic data to distribute vehicles on the simulated road section, c. computing an origin destination (OD) matrix according to the traffic data and distributing the traffic transportation flow of the simulated road section according to the OD matrix, and d. reproducing movement data of the simulated section according to the traffic transportation flow and based on a vehicle travel behavioral model of the traffic data.

Description

A kind of method that Expressway Traffic Flow reproduces

Technical field

The present invention relates to a kind of intelligent transportation emulation and reproduction field.

Background technology

In order to reflect more truly the situation of traffic, and dope exactly following congested in traffic problem according to real-time traffic data, now many external business microscopic traffic simulation softwares (as Paramics etc.) begin to attempt adopting the traffic data of Real-time Collection to be the basis, carry out the practice of in-circuit emulation aspect, the data of decision-making are provided for administrative authority more in time.The domestic research (as DynaCHINA) of also having carried out in this respect Used in Dynamic Traffic Assignment is based on real time data predict future traffic in short-term, as the foundation of dynamic traffic guidance.It is the basis of intelligent transportation system that real-time information accurately and short-time traffic flow forecast are provided, thereby has attracted numerous researchists to join in forecasting traffic flow research.Meanwhile, the traffic reproduction rarely had research.

Still there are the following problems for prior art: many stream, speed, the close relations of studying traffic flow from macroscopic perspective of existing traffic reproducting method, what pay close attention to is the lumped parameters such as average velocity, density, flow, is seeming not enough aspect the mutual relationship of the dynamic perfromance of simulating traffic flow and description surrounding vehicles and traffic environment.Microscopic Traffic Simulation Mathematic Model with the motion of each vehicle individuality on the road network space for finding the solution target, the dynamic perfromance of simulation traffic flow and the driver reaction to Way guidance.Therefore, be true reappearance traffic flow change in time and space, need to study the traffic reproducting method based on microscopic simulation.Use microcosmic traffic simulation system, can reproduce the time of day of traffic flow in the interaction of single unit vehicle rank patrix personification-Che-Lu, describe the implementation process of various traffic control strategies.

The present invention is directed to the characteristics of city expressway, proposed a kind of traffic behavior reproducting method based on microscopic simulation.This method is take the traffic flow statistics data that collect as the basis, the Kalman filtering method of select tape constraint calculates OD matrix between entrance, adopt the negative exponent distributed model to realize the initial distribution of road network vehicle, upgrade vehicle according to the vehicle production model of based on database, method by microscopic traffic simulation, the traffic behavior of true reappearance city expressway any time, and the movement locus that reappears vehicle.

Summary of the invention

For technological deficiency of the prior art, the invention provides a kind of method that Expressway Traffic Flow reproduces, it is characterized in that, comprising: a. obtains and treats the traffic data of emulation highway section within a time period; B. according to based on a vehicle production model of described traffic data, vehicle being distributed to described treating on the emulation highway section; C. calculate OD matrix and the traffic trip amount for the treatment of emulation highway section according to described OD matrix allocation according to described traffic data; D. reproduce vehicle at the described exercise data for the treatment of the emulation highway section according to described traffic trip amount with based on a Vehicle Driving Cycle behavior model of described traffic data.

Preferably, described traffic data obtains and is stored in database by being distributed in the coil for the treatment of the emulation highway section.

Preferably, described traffic data obtains and is stored in database by being distributed in the camera for the treatment of the emulation highway section.

Preferably, described traffic data comprises following one or more: type of vehicle; Vehicle average velocity; Time headway; Flow into the volume of traffic; And the outflow volume of traffic.

Preferably, the calculating of described vehicle production model comprises following one or more: calculate random vehicle; Calculate the random speed of a motor vehicle; Calculating is with motorcycle lane; And the stochastic distribution of calculating the original state vehicle.

Preferably, the stochastic distribution of described original state vehicle is calculated according to negative exponent time headway distributed model, and formula is as follows:

$f\left(t\right)=\frac{1}{T}{e}^{-t/T}$

The wherein distribution of .f (t) expression time headway, parameter T can by the observation sample Estimation of Mean, be calculated by following formula:

$T=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{t}_i$

Wherein, t ₁, t ₂... t _nFor the collection point is not collecting the time headway in this highway section in the same time, the number of times of n for gathering.

Preferably, described OD matrix calculates according to the constrained Kalman filter formula, and described constrained Kalman filter formula also comprises a perturbation matrix.

Preferably, described perturbation matrix is produced by white noise.

Preferably, described Vehicle Driving Cycle behavior model comprises following one or more: change model; Perhaps with speeding model.

The traffic flow statistics data that the present invention collects take coil are the basis, Kalman filtering method by belt restraining calculates OD matrix between entrance, adopt the negative exponent distributed model to realize the initial distribution of road network vehicle, upgrade vehicle according to the vehicle production model of based on database, method by microscopic traffic simulation, the traffic behavior of true reappearance city expressway any time, and the movement locus that reappears vehicle.

Description of drawings

By reading the detailed description of non-limiting example being done with reference to the following drawings, it is more obvious that other features, objects and advantages of the present invention will become:

Fig. 1 illustrates according to the first embodiment of the present invention, the process flow diagram that a kind of Expressway Traffic Flow reproduces:

Fig. 2 illustrates according to a second embodiment of the present invention, the calculation flow chart of vehicle production model;

Fig. 3 illustrates a third embodiment in accordance with the invention, forces to change the schematic diagram of model;

Fig. 4 illustrates a fourth embodiment in accordance with the invention, selects to change the schematic diagram of model; And

Fig. 5 illustrates according to a fifth embodiment of the invention, with the schematic diagram of the model of speeding.

Embodiment

By reading the detailed description of non-limiting example being done with reference to the following drawings, it is more obvious that other features, objects and advantages of the present invention will become:

Fig. 1 illustrates according to the first embodiment of the present invention, a kind of process flow diagram of Expressway Traffic Flow.Particularly, originally illustrating four steps, is at first step S101, obtains and treats the traffic data of emulation highway section within a time period, and particularly, this traffic data is historical traffic data.Treat the historical traffic data in emulation highway section preferably, obtain by being arranged on the coil collection for the treatment of the emulation highway section.Preferably, described coil is arranged at the place, gateway that treats the emulation highway section, is stored to after collection in a database.Preferably, the coil collection is through the volume of traffic of this coil.Perhaps, described traffic data is arranged on by one the camera head collection acquisition for the treatment of the emulation highway section.This camera head preferably is arranged at the place, gateway that treats the emulation highway section, is stored in a database after the collection traffic data.The camera head collection is through the volume of traffic of this camera head, and type of vehicle.Further, the traffic data of coil and camera head collection can also comprise average speed, and its implementation is as similar in the speed measuring device on existing highway section, does not repeat them here.Be step S102 afterwards, according to based on a vehicle production model of described traffic data, the vehicle initial distribution being treated on the emulation highway section to described.Particularly, the calculating of vehicle production model comprises five steps, specifically illustrates in Fig. 2.Execution in step S103, calculate OD matrix and the traffic trip amount for the treatment of emulation highway section according to described OD matrix allocation according to described traffic data afterwards.The OD matrix is important parameter in traffic engineering, play an important role in traffic programme, traffic administration and traffic control, in in the past 30 years, Chinese scholars uses many methods from the OD matrix of road section traffic volume flow data derivation traffic flow, method commonly used has generalized least square method, the entropy Maximum Approach, maximum likelihood estimation algorithm, bayesian theory method and Kalman Filter Estimation method etc.Least square method is away from simply; Entropy Maximum Approach, Maximum Likelihood Estimation and bayes method need data volume larger, and real-time is not strong, are difficult to follow the tracks of the continuous variation of traffic flow OD matrix, can not satisfy the needs of traffic control; Kalman filter method comes from modern control theory, relatively be suitable for the real-time estimation of Freeway OD matrices estimation, but the effect that conventional Kalman filtering can't be considered constraint condition therefore, and the present embodiment calculates by the constrained Kalman filter method of considering constraint condition the OD matrix for the treatment of the emulation highway section

Suppose that there are respectively m and n upper and lower ring road (main-inlet and primary outlet also are regarded as special ring road) in the through street road.According to front hypothesis, do not consider the hysteresis quality of traffic flow, this system at a time a section k have following relation:

y _ij(k)=r _i(k)a _ij(k)

In formula: y _ij(k) for to enter from i import ring road, the volume of traffic of selecting the j exit ramp to roll away from; r _i(k) volume of traffic for entering from i import ring road; a _ij(k) ratio of selecting the j exit ramp to leave for the volume of traffic that enters from i import ring road, i.e. ring road selection rate.Suppose r _i(i=1,2,3,4,5,6)

$\left(\begin{array}{c}{y}_1\\ y_2\\ y_3\\ y_4\\ y_5\\ y_6\\ y_7\end{array}\right)={\left(\begin{array}{cccccc}{a}_{11}& 0& 0& 0& 0& 0\\ a_{21}& a_{22}& 0& 0& 0& 0\\ a_{31}& a_{32}& 0& 0& 0& 0\\ a_{41}& a_{42}& a_{43}& a_{44}& 0& 0\\ a_{51}& a_{52}& a_{53}& a_{54}& a_{55}& 0\\ a_{61}& a_{62}& a_{63}& a_{64}& a_{65}& a_{66}\\ a_{71}& a_{72}& a_{73}& a_{74}& a_{75}& a_{76}\end{array}\right)}_{7\×6}\left(\begin{array}{c}{r}_1\\ r_2\\ r_3\\ r_4\\ r_5\\ r_6\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ {\mathrm{\ϵ}}_3\\ {\mathrm{\ϵ}}_4\\ {\mathrm{\ϵ}}_5\\ {\mathrm{\ϵ}}_6\\ {\mathrm{\ϵ}}_7\end{array}\right)$

The expression import, y _i(i=1,2,3,4,5,6,7) expression outlet.

By traffic information, can obtain following equation:

Consider the real-time of traffic, obtain following constraint:

Equation of constraint is:

A wherein _ijThe expression vehicle enters each probability that exports away from i from j entrance.Accordingly, just set up the primary relationship that linear fast road ramp flows into, flows out the volume of traffic.The problem of studying is that the volume of traffic of supposing the up and down ring road can obtain by the collection point, the inflow volume of traffic r (k) how basis detects, the anti-OD of the pushing away relation of outflow volume of traffic y (k), be ring road selection rate A (k), below we provide and use Kalman filtering to find the solution this problem.

Above-mentioned equation is converted into following form:

We are designated as it: Y=Ra+E, and wherein E is a perturbation matrix, the perturbation matrix that produces as white noise in calculating is below processed.We have just obtained the sky of former problem like this

${\left(\begin{array}{cccccccc}{\mathrm{<figure-callout\; id="1"\; label="r"\; filenames="HDA00002750829800031.png,HDA00002750829800032.png"\; state="\{\{state\}\}">r</figure-callout>}}_1& 0& 0& 0& ...& 0& 0& 0\\ 0& r_1& {\mathrm{<figure-callout\; id="2"\; label="r"\; filenames="HDA00002750829800011.png,HDA00002750829800021.png"\; state="\{\{state\}\}">r</figure-callout>}}_2& 0& ...& 0& 0& 0\\ ...& ...& ...& ...& ...& ...& ...& ...\\ 0& ...& r_1& r_2& r_3& r_4& r_5& r_6\end{array}\right)}_{7\&times;26}{\left(\begin{array}{c}{a}_{11}\\ a_{21}\\ a_{22}\\ ...\\ a_{76}\end{array}\right)}_{26\&times;1}+\left(\begin{array}{c}{\mathrm{\&epsiv;}}_1\\ {\mathrm{\&epsiv;}}_2\\ {\mathrm{\&epsiv;}}_3\\ {\mathrm{\&epsiv;}}_4\\ {\mathrm{\&epsiv;}}_5\\ {\mathrm{\&epsiv;}}_6\\ {\mathrm{\&epsiv;}}_7\end{array}\right)=\left(\begin{array}{c}{y}_1\\ y_2\\ y_3\\ y_4\\ y_5\\ y_6\\ y_7\end{array}\right)$

Between state equation, the relation that state equation reflection time-varying system internal state variable changes with current state, control inputs and system noise.Because the factor that affects the Freeway OD matrices estimation variation is many, and complicated, these factors are coupled again simultaneously, the relation of putting in order wherein is very difficult, or even impossible, therefore can reasonably simplify, make the clear legibility of problem, the while is undistorted real property again.At first, suppose that system noise is that average is 0 white noise sequence, and noise driving matrix is unit matrix.In fact this also can reflect the random fluctuation situation that arrives rate matrix to a great extent.Secondly, due to a lot of to the influence factor of OD coefficient, coupled relation is complicated again, be difficult to find out clear and definite influence factor, so can suppose that system is without control inputs, control inputs is implicit in system noise, state-transition matrix for system is difficult to resolve definite equally, but can think, in the situation that the research period is not very long, it is very little that the arrival rate matrix of two adjacent time intervals changes, and basically can think constant, therefore, can suppose that state-transition matrix is also unit matrix.

So we have iterative formula is Filtering Formula:

P _k+1,k=P _k+R _1,k

$K_{k+1}=P_{k+1,k}{R}_{k+1}^T(R_{k+1}{P}_{k+1,k}^T{R}_{k+1}+{\mathrm{<figure-callout\; id="2"\; label="R"\; filenames="HDA00002750829800011.png,HDA00002750829800021.png"\; state="\{\{state\}\}">R</figure-callout>}}_{2,k+1})$

Y _k+1,k=Y _k+1-R _k+1a _k

$a_{k+1}=a_k+K_{k+1}^T(Y_{k+1,k}-R_{k+1})a_k$

$P_{k+1}=\left[(I-K_{k+1})R_{k+1}^T\right]P_{k+1,k}$

Computation sequence is $P_{k+1,k}\&DoubleRightArrow;K_{k+1}\&DoubleRightArrow;P_{k+1}\&DoubleRightArrow;a_{k+1}.$ P wherein _{K+1, k}For utilizing a as a result of laststate prediction _k+1Covariance, P _kBe laststate optimal result a _kCovariance, P _k+1Be maximum likelihood estimate a _k+1Covariance, K _k+1Be kalman gain, R _k+1Be the parameter (being above-mentioned R matrix) of measuring system, R _{1, k}, R _{2, k+1}Be perturbation matrix.Utilize classical Kalman filtering algorithm herein, it will not go into details.R _{1, k}And R _{2, k}Perturbation matrix for the white noise generation.Further calculate the OD matrix after calculating the ring road selection rate according to the Kalman filtering formula that retrains, namely to all gateways, enter the volume of traffic of selecting the j exit ramp to roll away from from i import ring road.

Last execution in step S104 reproduces vehicle at the described exercise data for the treatment of the emulation highway section according to described traffic trip amount with based on a Vehicle Driving Cycle behavior model of described traffic data.Vehicle lane-changing model and vehicle follow gallop model have consisted of the Vehicle Driving Cycle behavior model jointly, be used for to describe the behavior of the people of emulation-Che unit, are important dynamic models in the multilane simulation model of microscopic.Owing to changing the environmental parameters such as the speed of a motor vehicle that involves the vehicle periphery vehicle, gap, thus the behavior of changing of vehicle than vehicle with speeding on as more complicated, and be difficult to describe with mathematical method.Changing is that the driver adjusts and complete the combined process of driving strategy according to the stimulation of own characteristic and ambient condition information, generally can be divided into information judgement and operation and carry out two processes.

Vehicle sails or rolls away from overtaking other vehicles of interwoven region, ring road and vehicle into and all must change, and the driver also can change when the speed of being discontented with oneself is subject to the restriction of front truck.The behavior of changing under different situations has very large difference in driving behavior, need to adopt the different models that changes to be described.Whether be necessary according to the behavior of changing, can be divided into that judgement property is changed and enforcement zone is changed with changing.Vehicle change model with respect to relatively lagging behind with the model developments of speeding, until the U.S. in 1985 is for the needs of microscopic traffic simulation research, after adopting the aerial survey means to set up microcosmic traffic vehicle movement information database, changing model has just had significant progress.The early stage behavioral study that changes has Gipps model, NETSIM model and FRESIM model, and the models such as SITRAS have been arranged again afterwards.Not having the behavior of changing in fixed target track all to belong to judgement property changes.In judgement property was changed model, changing needed experienced three stages: first the wish of changing according to the driver judges whether the demand of changing trains; Estimate whether satisfy the condition of changing according to neutral gear between vehicle and length velocity relation again; Change later in the satisfied condition of changing at last and process or do not satisfy vehicle continuation and travel by original transport condition.The below is from demand generation, gap detection and change and carry out three aspect introductions judgement property and change model.

The generation of changing at present demand mainly contains two kinds of algorithms: PLC method and comprehensive evaluation.PLC(probability of lane changing) be the concept of changing probability, this method is to use simple driver's satisfactory state statistics to change the condition of demand as generation.

After having produced the demand of changing, just can change and to carry out gap detection.Vehicle lane-changing can cause the variation of vehicle follow gallop state, so gap detection needs and is in the same place with the models coupling of speeding.The model of INTRAS and WEAVSIM has all used such method: judge that can main car safely follow car owner's car with the rear car in the front truck in the target track of speeding and target track.If the request of changing of accepting is satisfied in the safety clearance.

Execution is changed generally dual mode: a kind of is the emulation of changing track, describes the behavior of changing of vehicle in detail from the relation of driving drift angle and the speed of a motor vehicle; Another kind is to provide one to change the time T of completing to need, after elapsed time section T, and vehicle target approach track, and need not consider the detailed process of vehicle lane-changing.More general being utilized of a kind of rear method.

Fig. 2 illustrates according to a second embodiment of the present invention, the calculation flow chart of vehicle production model.This figure shows 5 steps altogether, is at first step S201, reads the traffic data of a certain period, and step S202 calculates random type of vehicle.Step S203 calculates the random speed of a motor vehicle.Step S204 calculates with motorcycle lane.Step S205, the stochastic distribution of calculating original state vehicle.Particularly, it will be appreciated by those skilled in the art that the vehicle production model is the most basic model of Microscopic Traffic Simulation Mathematic Model, the input problem of main transport solution stream.In the traffic flow of reality, the arrival of vehicle is random, discrete, therefore the vehicle production model is certain time period that needs the user to specify needs to reproduce, then system is by the traffic data of this time period in reading database, as the volume of traffic, type of vehicle, vehicle average velocity etc., and to these data analysis, calculate at last the original state of vehicle.Owing to being accurate reproduction to the magnitude of traffic flow, in order to reach effect true to nature, must be distributed to certain vehicle flowrate on road network at the very start in emulation, rather than begin to put forward from certain highway section, therefore vehicle production model of the present invention not only comprises random vehicle, with the calculating of motorcycle lane, also to comprise the stochastic distribution of emulation original state vehicle.

For Microscopic Traffic Simulation Mathematic Model is simulated really, must carry out random sampling, produce in other words and obey certain stochastic variable that distributes.All between [0,1], therefore, can be obtained by arbitrary numerical value between [0,1] value of stochastic variable by inversion method, transformation method, combined method, pass-fail and method of approximation due to the codomain of any probability distribution function.Therefore, correct [0,1] the upper uniform random number that generates just becomes the basis that produces all stochastic variables, if there is no good pseudorandom number generator, just is difficult to obtain correct stochastic variable.The pseudorandom number generator that the present embodiment preferably adopts is Linear Congruential Generator.Its recursion formula is:

$\left\{\begin{array}{c}{X}_i=({\mathrm{aX}}_{i-1}+c)\left(\mathrm{mod}m\right)\\ u_i=X_i/m\\ X_0\end{array}(i=\mathrm{1,2},...)\right.$

Wherein, m is modulus, and a is multiplier, and c is increment, and m, a, c are nonnegative number; X ₀Be initial value, and be nonnegative number; u _iBe the last random number that produces.

Random number is calculated random type of vehicle after generating, and in general microscopic traffic simulation, vehicle generally is divided into cart, common car (middle car) and dolly three types.Wherein, the length of wagon of cart is generally greater than 8m, and generally between 3m and 8m, the length of wagon of dolly is generally less than 3m to the length of wagon of common car.If in vehicle, the number percent of cart is p1, the number percent of middle car is p2, and the number percent of dolly is that p3(can also add other vehicle according to actual conditions), p1+p2+p3=1 so.Represent the appearance situation of vehicle in wagon flow with stochastic variable X, X=0 represents cart, car during X=1 represents, and X=2 represents dolly.

So the probability density function of stochastic variable X is:

$f\left(x\right)=\left\{\begin{array}{c}p(X=0)=p1\\ p(X=1)=p2\\ P(X=2)=p3\end{array}\right.$

The probability distribution function F (x) of stochastic variable X is:

$F\left(x\right)=\left\{\begin{array}{cc}0& x<0\\ \mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HDA00002750829800031.png,HDA00002750829800032.png"\; state="\{\{state\}\}">p</figure-callout>}1& 0\&le;x<1\\ \mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HDA00002750829800031.png,HDA00002750829800032.png"\; state="\{\{state\}\}">p</figure-callout>}1+\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HDA00002750829800011.png,HDA00002750829800021.png"\; state="\{\{state\}\}">p</figure-callout>}2& 1\&le;x<2\\ \mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HDA00002750829800031.png,HDA00002750829800032.png"\; state="\{\{state\}\}">p</figure-callout>}1+\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HDA00002750829800011.png,HDA00002750829800021.png"\; state="\{\{state\}\}">p</figure-callout>}2+p3& 2\&le;x<3\end{array}\right.$

If u (x) is the random number between 0 to 3:

Be the calculating of the random speed of a motor vehicle afterwards, studies show that speed compliance normal distribution or lognormal distribution on road, but because normal distyribution function can't carry out inversion, thus transformation method generally adopted, when X ~ N (0,1), Y ~ N (μ, σ ²), be expressed as:

Y=σX+μ

So, adopt transformation method, only need to produce two equally distributed random function u ₁, u ₂, can produce a stochastic variable Z who obeys standardized normal distribution, and the initial velocity v of vehicle, its expression formula is

$\left\{\begin{array}{c}Z=\sqrt{-2\ln \left(u_1\right)}\cos \left({2\mathrm{\&pi;u}}_2\right)\\ v=u+\mathrm{\&sigma;}*Z\end{array}\right.$

Wherein: u ₁, u ₂Represent two equally distributed random numbers; U represents the speed average; σ represents the speed mean variance.

The stochastic distribution of calculating vehicle original state after the random speed of a motor vehicle is calculated and completed, wherein the time headway distribution is an important content of traffic flow theory research, and it is the basis of Traffic Capacity Analysis, gap acceptance Study on Problems, crossing traffic control and traffic simulation.For the traffic flow simulation, time headway distribution and operating automation thereof have decisive meaning for the simulation capacity of traffic flow simulation system especially.According to different traffic characteristics, the researchist has proposed the very strong model of a lot of practicality, as early stage for the negative exponent time headway distributed model under freestream conditions, and displacement negative exponent model.Increase along with the road traffic load in order to describe corresponding rule, has proposed the models such as Irish distribution, lognormal distribution, M3 distribution.

Roughly calculate the saturation volume S at crossing with the Webster method according to the road geometric parameter, draw the vehicle flowrate q of every road by the OD matrix, ratio between two q/S is throughput ratio y (or claiming saturation degree), and which kind of discrete distribution judgement adopts accordingly.If the vehicle flowrate of input is significantly less than saturation volume, and other parts seldom have traffic signals except simulated domain, that is to say, other zone mostly is the crossing that no signal is controlled, average and the variance of vehicle arrival number are substantially equal like this, select Poisson distribution; Poisson distribution is successfully used to describe the vehicle number that sets out of source node in continuous time interval, and this count distribution corresponding (time headway distribution) spaced apart is exactly that negative exponent distributes.If the OD matrix of input comprises peak period and non-peak period two parts, namely the volume of traffic is very large for some time, and a period of time volume of traffic is very little, just selects negative binomial distribution; Also have a kind of situation, the process simulation highway section is positioned at the downstream of whole road grid traffic wire size, and the first half section volume of traffic of signal period is large, and the second half section volume of traffic is little, also is fit to binomial distribution; When the magnitude of traffic flow is very large, approach or surpass saturation volume, at this time the vehicle chance of freely travelling is few, and the variance of vehicle arrival number so just should be used binomial distribution less than average.

Based on above description, the present invention is the traffic data of through street due to what adopt, the time headway model that therefore adopts negative exponent to distribute, and formula is as follows:

The wherein distribution of .f (t) expression time headway, parameter T can by the observation sample Estimation of Mean, be calculated by following formula:

$T=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{t}_i$

Wherein, t ₁, t ₂... t _nBe the number of times that gathers at the time headway n that does not collect in the same time this highway section for the collection point.。

Further, it will be appreciated by those skilled in the art that above-mentioned steps S202, S203, the computation sequence of S204 and S205 is not limited in shown in the present embodiment.Particularly, when the traffic data that obtains comprised type of vehicle, above-mentioned steps S202 can omit; When the traffic data that obtains comprised vehicle average velocity, above-mentioned steps S203 can omit, and particularly, did not repeat them here.

Particularly, Vehicle Driving Cycle behavior model provided by the invention preferably, has adopted enforcement zone to change model and selectivity is changed model.Preferably, change model and comprise that enforcement zone is changed model and selectivity is changed model.

The judgement that the changing of enforcement zone do not need the demand of changing to produce, vehicle enter had when forcing to change the district determine change the target track.Forcing to change the zone, vehicle ceaselessly detects the neutral gear in target track and speed and the distance of front and back car, judges whether to satisfy the condition of changing of vehicle.Change behavior if condition is satisfied to carry out, do not continue to detect judgement if the condition of changing does not satisfy, change until be successfully completed.

If when front truck can't successfully arrive next track or the place ahead accident without continue to travel, at this moment just need to force to change in order to can enter smoothly next track when front truck, be illustrated in figure 3 as the mandatory schematic diagram that changes.

Target vehicle produced at once and forced the consciousness of changing this moment, and with retarded velocity a _nReduce speed now, a _nExpression formula be:

$a_n=-\frac{{\mathrm{<figure-callout\; id="2"\; label="v\; n"\; filenames="HDA00002750829800011.png,HDA00002750829800021.png"\; state="\{\{state\}\}">v</figure-callout>}}_n^{}}{2(l_n-\mathrm{\&sigma;})}$

Wherein: v _nExpression is when the travel speed of front truck; l _nExpression is when the distance of leading vehicle distance entrance or outlet; σ represents to stop when front truck σ rice before accident spot.

Because embodiment only considers entrance and exit, do not consider that any traffic hazard occurs, so σ is not discussed.

When working as front truck with retarded velocity a _nWhen reducing speed now, beginning constantly checks whether the spacing with rear car satisfies the condition in its conversion road, i.e. judgement with the spacing of rear car whether more than or equal to necessary following distance.Wherein necessary following distance is determined according to being: will change on adjacent lane if work as front truck, it should be the front truck as oneself with the front truck on adjacent lane, and the rear car on adjacent lane is rear with car as oneself.Change desired following distance if satisfied with the spacing of rear car, when front truck will no longer give it the gun, change requirement then whether satisfy it with car after judgement.If with the rear requirement of also satisfying car-following model with the spacing of car, change when front truck, otherwise, when front truck send change signal to after with car, and slow down with car after waiting for, until satisfy change condition till.

In sum, when vehicle enter force to change the district after, produce immediately and force lane-changing intention, then reduce speed now, and the select target track, after the target track is determined, then judge that it changes requirement with the following distance of front and back car on the target track is whether satisfied.If all satisfy with the spacing of front and back car the condition of changing, change immediately, otherwise then judgement and the following distance of front and back car respectively to be changed requirement if do not satisfy with the spacing of front truck, it will continue deceleration; Change requirement if do not satisfy with the following distance of rear car, it just backward car send the request of changing, until satisfy change condition till.

It is restriction due to front truck that selectivity is changed, and can not reach the desired speed of oneself when front truck, and adjacent lane has higher driving satisfaction than current track, at this moment when might carrying out selectivity, changes front truck, as shown in Figure 4:

In the process that selectivity is changed, at first whether the driver is satisfied with to current track and assesses, if work as the speed v of front truck _nSpeed v greater than the place ahead car _n-1And with the distance of the place ahead car during less than certain value, generate the demand of changing, subsequently to adjacent lane on the spacing of front and back car judge, can analysis realize changing, if satisfy begin to change, if with the distance of adjacent lane front truck less than changing required separation distance, it will slow down, until till satisfying vehicle headway.When with the spacing of front truck satisfy change require after, when front truck judges it changes required separation distance with whether also satisfying with the spacing of car afterwards, if do not satisfy, it will continue to travel with existing speed, and give to send with car afterwards and ask to change signal again.Rear with car with certain Probability p _n+1Select whether to slow down with to abdicating enough neutral gears when front truck, it is changed.P wherein _n+1Expression formula be:

$p_{n+1}=\min (0.75,\mathrm{\&alpha;}(v_n-v_n^0)\left(1.5\text{-\&theta;}\right))$

Here α represents systematic parameter, and generally getting 0.2, θ is driver's impulsion coefficient.

The behavior of changing can be regarded as the transformation of vehicle follow gallop behavior, changes the front truck in target track with relaxing by becoming with the front truck in current track of speeding, thus can with can be safely with speed as judgement change can security implementation standard.

The present embodiment changes model and preferably uses following principle:

(1) if when front truck and front following distance or with after arbitrary spacing in following distance be rejected cancel and changing;

(2) enter when forcing to change the district when front truck, obtain to force to change signal, and begin to carry out mandatory changing, if when the speed of the front truck speed greater than front truck.And distance is only carried out take the raising speed of a motor vehicle as the judgement of purpose and is changed greater than safe distance:

The purpose of 1. forcing to change is the correct next highway section that arrives travel route;

2. judge that the purpose of changing is the slow train that vehicle is wished to improve the speed of a motor vehicle or surpassed the place ahead;

(3) vehicle changes at every turn, is merely able to change to adjacent lane, if non-conterminous when track and the target track at front truck place, needs through repeatedly changing;

(4) carry out 2s and change principle.

The present embodiment vehicle follow gallop model preferably adopts classical safe distance with speeding model, Safety distance model is also referred to as crashproof model, be called for short the CA model), the most basic relation of this model is to seek a specific distance of speeding of following, collision can be in time slowed down and be prevented in the beyond thought action of car driver after the front truck driver has made, rear car.Initial mask suc as formula shown in:

$\mathrm{\&Delta;x}(t-T)={\mathrm{av}}_{n-1}^2(t-T)+{\mathrm{\&beta;}}_l{v}_n^2\left(t\right)+{\mathrm{\&beta;v}}_n\left(t\right)+b_0$

Wherein: a, β _l, β, b ₀Be parameter.

Safety distance model has a wide range of applications in Computer Simulation.As the McDonald of Department for Transport, the SISTM model of Brackstone and Jefery, the calculated Broqua of Italian, French PROMETHEUS, Lemer, the SPACES model of Mauro and Morell, the Benekohal of the U.S. and the INTRAS of Treiterer and CARSIM model.Nineteen ninety-five, the Kumamoto of Japan, Nishi, Tenmoku and Shimoura also use this class model and carry out emulation.Why this class model has so large attractive force, and partly cause is and can comes peg model to the general perception hypothesis of driving behavior with some.Only need to know that in most cases the driver with the maximum braking deceleration that adopts, just can satisfy the needs of whole model.Although this model can draw the result of making us accepting, still have a lot of problems to have to be solved, for example, the hypothesis of avoiding colliding is reasonable in the foundation of model, but exists gap with actual conditions; In the traffic circulation of reality, the driver does not keep a safe distance under many circumstances and travels, the reason that causes this situation is many-sided, can see front signal lamp and a more than front guide-car as the driver, after the driver comprehensively judges these information, can in time make prediction to front guide-car's variation.Therefore, when utilizing the CA model to carry out Traffic Capacity Analysis, be difficult to coincide with the actual maximum volume of traffic.

The present embodiment will be divided into three phases namely with the model of speeding: conventional with speeding stage, free enforcement stage, emergency brake stage.Before supposing, vehicle speed is V, is in the graph of a relation of the relative velocity of front and back car of the state of speeding and relative distance as shown in Figure 5.The C point is the expectation spacing of front and back two cars, and A is the minimum spacing of front and back two cars, and B is the maximum spacing of two cars.Being the emergency brake stage when spacing during less than OA, is free travel phase when spacing during greater than OB, when spacing is between AB for conventional with speeding the stage.Mechanism of perception during according to observer in the visually-perceptible ecological theory of J.J.Gibson and environment generation relative motion is known AC＜CB, and AC and the value of CB are the random values relevant with driver's individual character.Therefore, the vehicle follow gallop problem can be converted into according to time headway and ask the vehicle acceleration problem.

According to the data of front, with time headway〉state of 5s is defined as free travel phase, and its Acceleration Formula is:

$a=\left\{\begin{array}{cc}{a}_0\frac{v_{\exp }-v}{v_{\exp }}& v<v_{\exp }\\ a_0\frac{v-v_{\exp }}{v}& v>v_{\exp }\end{array}\right.$

Wherein: a ₀Initial acceleration; v _expDesired speed when the front truck free walker is sailed; V is when the speed of vehicle; The acceleration that a should take when front truck.

When time headway＜0.5s, this moment, vehicle was in a state of emergency, i.e. in the emergency brake stage, after this moment, car must adopt suitable retarded velocity to increase the distance with front truck, until enter in safe range.Its retarded velocity formula is as follows:

$a_n=\left\{\begin{array}{cc}\min \{a_n^{-},a_{n-1}+0.25a_n^{-}\}& v_n\&le;v_{n-1}\\ \min \{a_n^{-},a_{n-1}-0.5{(v_n-v_{n-1})}^2/g_n\}& v_n>v_{n-1}\end{array}\right.$

Wherein: a _nThe acceleration that should take for rear car; a _nBe the current acceleration of rear car; a _n-1Be the acceleration when front truck; v _nRear car present speed; v _n-1The front truck present speed; g _nThe clear distance of front and back two cars.

When time headway be in greater than 5s less than 0.5s between the time, this moment, the speed of Vehicle Driving Cycle and the kinematic behavior that acceleration is subjected to front truck affected, vehicle is in oscillation phase, follows with conventional the definition with the scheme of speeding the model of speeding.

OD matrix and above-mentioned vehicle behavior running model that the time headway that the traffic data that integrating step S101 of the present invention obtains, step S102 calculate, S103 calculate have been reproduced vehicle at the described exercise data for the treatment of the emulation highway section.Particularly, the present invention uses microcosmic traffic simulation system, can in the interaction of single unit vehicle rank patrix personification-Che-Lu, effectively utilize the data that coil and camera head gather, reproduce the time of day of traffic flow, describe the implementation process of various traffic control strategies.It is take single unit vehicle as object, vehicle on road with car, overtake other vehicles and the microscopic behavior such as lane changing behavior can both reflect very careful and really, and show with the form of dynamic image, for the adjustment of traffic control strategy, implement to provide reference intuitively.the reproduction for the treatment of the emulation highway section based on certain period, eliminating existing traffic system can't carry out in advance arrange combination and the current control of the efficient vertical or horizontal oldered array of order to wagon flow and induce, and conflict removal disturbs, or elimination can not take full advantage of the crossing, the drawbacks such as the passage space in highway section, improve going through ability, reduce and incur loss through delay, thereby solve the concrete technical problems of alleviating traffic congestion, the resulting various data of emulation can be used for the analysis to traffic, prediction, the traffic administration control program is assessed, for the traffic route management planning provides technical basis, design proposal to various means of transportation, management and control measure and Transportation Demand Management scheme are estimated.

Above specific embodiments of the invention are described.It will be appreciated that, the present invention is not limited to above-mentioned specific implementations, and those skilled in the art can make various distortion or modification within the scope of the claims, and this does not affect flesh and blood of the present invention.

Claims (9)

1. the method that Expressway Traffic Flow reproduces, is characterized in that, comprising:

A. obtain and treat the traffic data of emulation highway section within a time period;

B. according to based on a vehicle production model of described traffic data, vehicle being distributed to described treating on the emulation highway section;

C. calculate OD matrix and the traffic trip amount for the treatment of emulation highway section according to described OD matrix allocation according to described traffic data;

D. reproduce vehicle at the described exercise data for the treatment of the emulation highway section according to described traffic trip amount with based on a Vehicle Driving Cycle behavior model of described traffic data.

2. method according to claim 1, is characterized in that, described traffic data obtains and is stored in database by being distributed in the coil for the treatment of the emulation highway section.

3. method according to claim 1, is characterized in that, described traffic data obtains and is stored in database by being distributed in the camera for the treatment of the emulation highway section.

4. method according to claim 1, is characterized in that, described traffic data comprises following one or more:

Type of vehicle;

Vehicle average velocity;

Time headway;

Flow into the volume of traffic; And

Flow out the volume of traffic.

5. method according to claim 1, is characterized in that, the calculating of described vehicle production model comprises following one or more:

Calculate random vehicle;

Calculate the random speed of a motor vehicle;

Calculating is with motorcycle lane; And

Calculate the stochastic distribution of original state vehicle.

6. method according to claim 5, is characterized in that, the stochastic distribution of described original state vehicle is calculated according to negative exponent time headway distributed model, and formula is as follows:

$f\left(t\right)=\frac{1}{T}{e}^{-t/T}$

The wherein distribution of .f (t) expression time headway, parameter T can by the observation sample Estimation of Mean, be calculated by following formula:

$T=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{t}_i$

Wherein, t ₁, t ₂... t _nFor the collection point is not collecting the time headway in this highway section in the same time, the number of times of n for gathering.

7. method according to claim 1, is characterized in that, described OD matrix calculates according to the constrained Kalman filter formula, and described constrained Kalman filter formula also comprises a perturbation matrix.

8. method according to claim 7, is characterized in that, described perturbation matrix is produced by white noise.

9. method according to claim 1, is characterized in that, described Vehicle Driving Cycle behavior model comprises following one or more:

Change model; Perhaps

With speeding model.

Images