CN103226893A - Method and simulation system for describing traffic flow behavior based on two-dimensional macroscopic flow model - Google Patents

Abstract

The invention provides a method and a simulation system for describing a traffic flow behavior based on a two-dimensional macroscopic flow model. The method comprises the steps that 1, grid dissection is conducted on a pavement based on a two-dimensional highway plane; a two-dimensional road network is constructed; traffic flow information in the two-dimensional road network at the initial time is mapped to a corresponding grid of the two-dimensional road network; 2, traffic flow information in each grid in the two-dimensional road network at next time is calculated according to the two-dimensional macroscopic flow model; and 3, a state of a vehicle in the two-dimensional road network is updated according to the traffic flow information in each grid in the two-dimensional road network at next time, and is displayed in a three-dimensional scene.

Description

Method and simulation system based on two-dimentional macroscopic flow model description traffic flow behavior

Technical field

The present invention relates to traffic and transport field and field of Computer Graphics, relate in particular to a kind of method and simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description.

Background technology

To the mathematical description of traffic flow behavior in the road, can be used for the computer simulation of traffic problems analysis and traffic behavior.In actual life, surpass 5,000,000 as Beijing vehicle population, through street, heart of Beijing city total kilometrage is above 310 kilometers.And the traffic behavior and the road conditions that have various complexity in the road network, for example traffic hazard, viaduct, crossroad, interim traffic control etc.So mathematical model not only needs to describe the traffic behavior of extensive vehicle, also the different motion behavior of vehicle in complicated traffic network must be described, as quickening, slow down, keep straight on, change trains etc.

The existing method that is used to describe extensive vehicle mainly is the macroscopic flow method.These class methods can well be described the acceleration of vehicle, behaviors such as deceleration.But existing macroscopic flow method nearly all is to use along the one dimension fluid model of lane line to describe vehicle moving on highway plane.Model is mutual for the wagon flow between the track, can only provide wagon flow by the experience assignment and when begin to flow out current track, flows out the lasting time etc.So can only provide rough calculating alternately to the wagon flow between two tracks, can not effectively calculate wagon flow and when begin to flow out, flow out the time that continues, final discharge etc.In the actual traffic, there is a large amount of ring road gateways in the road network, crossroad, track doubling, traffic control, complicated traffic such as traffic hazard.At these places, highway section, exist a large amount of vehicles to flow into (outflow) between the track.The effective wagon flow interbehavior between simulated roadway, the traffic conditions in this part highway section of fine simulation of just having no idea, thus influence the analog result of whole road grid traffic situation.

How effectively describe wagon flow interbehavior between the track, make the analog result reality of more fitting with the macroscopic flow model.This problem never is resolved.

Summary of the invention

For addressing the above problem, the invention provides a kind of method and simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description, the wagon flow motion of road along the line direction can not only be described, wagon flow motion between the track can also well be described, and when have the outflow of wagon flow, the time that outflow continues, the final flow that flows out to draw on the current track by finding the solution this two dimension macroscopic flow model, can strengthen the confidence level of analog result greatly.

For achieving the above object, the invention provides a kind of method based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description, this method comprises:

Step 1 is carried out mesh generation based on two-dimentional highway plane road pavement and is made up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Step 2 is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

Step 3, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

Step 4, repeated execution of steps 2,3 is to carry out the timing simulation of wagon flow behavior.

Further, in the described two-dimentional macroscopic flow model:

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

ρ wherein _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

Further, the n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

Further, if there is extraneous wagon flow to flow into current described two-dimentional road network, be translated into boundary condition treatment.

For achieving the above object, the present invention also provides a kind of simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description, and this simulation system comprises:

The two dimension road network makes up module, carries out mesh generation based on two-dimentional highway plane road pavement and makes up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Model computation module is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

The update displayed module, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

The timing simulation module repeats model computation module and update displayed module to carry out the timing simulation of wagon flow behavior.

Further, in the described two-dimentional macroscopic flow model:

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

ρ wherein _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

Further, the n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

Further, if there is extraneous wagon flow to flow into current described two-dimentional road network, be translated into boundary condition treatment.

Beneficial effect of the present invention is:

1) (x y) goes up the two-dimentional macroscopic flow model description traffic flow behavior of adopting at two-dimensional space.The traffic flow modes of current location not only depends on the traffic state on the current track, also depends on the traffic state on the track on every side.

2) two-dimentional macroscopic flow model no longer is to adopt along lane line direction situation

Wagon flow is to the optimization of current location traffic state, but the traffic state on the employing current location wagon flow direction

Current traffic state is optimized.This two dimension macroscopic flow model not only can well be described the wagon flow motion of road along the line direction, can also well describe the wagon flow motion between the track.When there are the outflow of wagon flow, the time that outflow continues, the final flow that flows out to draw by finding the solution this two dimension macroscopic flow model on the current track.

3) two-dimentional macroscopic flow modeling result has obtained showing intuitively, has strengthened the confidence level of analog result.

Describe the present invention below in conjunction with the drawings and specific embodiments, but not as a limitation of the invention.

Description of drawings

Fig. 1 is a road surface of the present invention mesh generation synoptic diagram;

Fig. 2 is a road road network synoptic diagram of the present invention;

Fig. 3 is a wagon flow speed density initialization synoptic diagram of the present invention;

Fig. 4 is the method flow diagram based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description of the present invention;

Fig. 5 is the simulation system synoptic diagram based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description of the present invention.

Embodiment

The objective of the invention is to solve in the existing macroscopic traffic flow and can't effectively describe the mutual problem of wagon flow between the track.Fig. 4 is the method flow diagram based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description of the present invention.As shown in Figure 4, this method comprises:

Step 1 is carried out mesh generation based on two-dimentional highway plane road pavement and is made up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Step 2 is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

Step 3, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

Step 4, repeated execution of steps 2,3 is to carry out the timing simulation of wagon flow behavior.

Further, described

In the two dimension macroscopic flow model:

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

ρ wherein _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

Further, the n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

Further, if there is extraneous wagon flow to flow into current described two-dimentional road network, be translated into boundary condition treatment.

Fig. 5 is the simulation system synoptic diagram based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description of the present invention.As shown in Figure 5, this simulation system comprises:

The two dimension road network makes up module 100, carries out mesh generation based on two-dimentional highway plane road pavement and makes up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Model computation module 200 is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

Update displayed module 300, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

Timing simulation module 400 repeats model computation module and update displayed module to carry out the timing simulation of wagon flow behavior.

Further, described

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

Wherein, ρ _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

Further, the n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

Further, if there is extraneous wagon flow to flow into current described two-dimentional road network, be translated into boundary condition treatment.

The two-dimentional macroscopic flow model of description large-scale complex traffic flow behavior disclosed in this invention comprises following three parts: the structure of two-dimentional road network and traffic flow modes initialization, road grid traffic stream mode are upgraded, vehicle upgrades oneself state according to traffic flow modes.Wherein:

What 1) structure of two-dimentional road network and traffic flow modes initialization section mainly realized is that road network topology structure and traffic behavior are mapped on the information of traffic-flow models in two dimensions description.What this step was done is the data preliminary works.Specifically comprise following steps:

1) based on two-dimentional highway plane (having lane line number 〉=1), road pavement is carried out mesh generation (as shown in Figure 1, Fig. 1 is a road surface of the present invention mesh generation synoptic diagram);

2) traffic flow situation initialization in the road network.Specifically refer to the wagon flow traffic conditions (number of vehicles and speed) at the each point place in the initial time road network is mapped to each grid according to certain requirement;

3) calculate or estimate the traffic flow density in the road network under the normal condition, driving speed limit, general three parameter values of driving vehicle type (vehicle length) according to the traffic in the time in the past in the road network.

The road network subdivision is along the subdivision of lane line tangential direction with perpendicular to the normal direction subdivision of lane line, thus obtain mesh node (j, m).The step sizes of normal direction subdivision is the width of lane line, and tangential subdivision step-length (being made as Δ x) size requires according to accuracy of simulation and the stability requirement of formula (1) value within the specific limits.

Two dimension macroscopic flow model is value information just, as emulation initial time t=t ₀The time road network in wagon flow speed v (x, y, the t of position ₀), density p (x, y, t ₀) wait in the following way and provide: according to the vehicle position and the speed conditions that distribute in the current time road network, try to achieve the wagon flow speed and the density at each grid place, as shown in Figure 2.In the reality, have spacing between vehicle and the vehicle, we adopt following method that wagon flow speed, the density of all positions on the road are carried out assignment: with Δ x at interval, ask the number and the average speed of vehicle in this step-length, as shown in Figure 3, the vehicle commander of vehicle a and vehicle b is L, and the speed of a motor vehicle is respectively v _aAnd v _bIf (in the coarse line region) comprises a vehicle vehicle commander's 1/3 in the current step-length, b vehicle commander's 1/2, the wagon flow speed of all positions all is in the then current step-length

Density is

If do not have vehicle in the current step-length, then wagon flow speed is the maximum speed limit in highway section, and density is 0.

2) the road network traffic flow state updating section mainly realizes is wagon flow traffic according to position in the current time road network, finds the solution next wagon flow traffic of position in road network constantly, specifically comprises following steps:

1) size and following formula (1) stable constraint according to the road network grid subdivision draws current time and next maximum delay time τ constantly;

2) adopt certain numerical computation method according to following two-dimentional macroscopic flow model, calculate next interior wagon flow traffic conditions (density p (x, y, t+ τ) and speed v (x, y, t+ τ)) of interior each grid of road network constantly:

$\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.---\left(1\right)$

The model medium velocity all was different along value in the one-dimensional space of lane line direction with density in the past, our two-dimentional macroscopic flow model medium velocity v (x, y, t) and density p (x, y t) are value in two-dimensional space.Be v (x, y, t) expression t moment two-dimensional space (x, the y) speed of position wagon flow, ρ (x, y, t) expression t moment two-dimensional space (x, y) density of position wagon flow.Second equation is as the difference equation of optimizing the wagon flow state, ρ in the two dimension macroscopic flow model _{J, m}(t) and υ _{J, m}(t) node (j, density of m) locating and speed on the expression two-dimensional space road surface.ρ ₀Be constant, represent the average density of current highway section wagon flow, need provide as initial value.τ is time delay, by the character decision of choosing different method of value solving.V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information.Optimal speed function in the model all was to adopt along the wagon flow on the lane line direction current wagon flow to be optimized in the past, and our two-dimentional macroscopic flow model is to adopt the wagon flow on the current location wagon flow direction that the traffic state of current location is optimized.Wherein,

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

Parameter n, β _l, ρ _c, v _MaxBe constant, need provide as initial value.Usually the n value is 3, and is corresponding ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3.ρ _cBe the inverse of safe distance between vehicles, value is 0.2vel./m usually.v _MaxBe the maximum speed limit in current highway section, general value is the desired speed of vehicle.

After above-mentioned equation is provided with suitable first value information (is the initial time traffic flow modes, density everywhere and speed), by adopting effective method of value solving (for example finite difference method), two-dimentional macroscopic flow model equation is found the solution, can obtain the wagon flow speed of follow-up each position of the moment, density information is realized the analog computation of traffic flow.

If have extraneous vehicle to flow into current road network in the simulation time.Above-mentioned two-dimentional macroscopic flow model is translated into boundary condition treatment in the following way: to scheme road net data is example, the road network boundary is if there is vehicle to flow into, suppose to flow into a car on every track of current boundary in the average delta t time, the influx in the per second of then current track is 1/ Δ t.

3) vehicle upgrades the oneself state part according to traffic flow modes main what realize is that macroscopical traffic flow situation is mapped to each car, to reach the demonstration directly perceived of traffic, specifically comprises following steps:

1) vehicle upgrades oneself state according to next state (last branch calculates and obtains) constantly of place grid;

2) with the position display behind the vehicle replacement in three-dimensional scenic.

What this part was mainly done is the demonstration directly perceived of analog result, has strengthened the confidence level of analog result.The information that vehicle can access numerical algorithm direct and that formula (1) adopts has relation.

Certainly; the present invention also can have other various embodiments; under the situation that does not deviate from spirit of the present invention and essence thereof; those of ordinary skill in the art work as can make various corresponding changes and distortion according to the present invention, but these corresponding changes and distortion all should belong to the protection domain of the appended claim of the present invention.

Claims (8)

1. the method based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description is characterized in that, comprising:

Step 1 is carried out mesh generation based on two-dimentional highway plane road pavement and is made up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Step 2 is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_1{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

Step 3, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

Step 4, repeated execution of steps 2,3 is to carry out the timing simulation of wagon flow behavior.

2. the method based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 1 is characterized in that, and is described

In the two dimension macroscopic flow model:

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

ρ wherein _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

3. the method based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 1 is characterized in that, if there is extraneous wagon flow to flow into current described two-dimentional road network, is translated into boundary condition treatment.

4. the method based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 2 is characterized in that,

The n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

5. the simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description is characterized in that, comprising:

The two dimension road network makes up module, carries out mesh generation based on two-dimentional highway plane road pavement and makes up two-dimentional road network, and the wagon flow transport information in the initial time two dimension road network is mapped on the corresponding grid of described two-dimentional road network;

Model computation module is according to two-dimentional macroscopic flow model $\left\{\begin{array}{c}{\∂}_t\mathrm{\ρ}(x,y,t)+\▿\left(\mathrm{\ρ}(x,y,t)\mathrm{\υ}(x,y,t)\right)=0\\ {\mathrm{\ρ}}_{j,m}(t+\mathrm{\τ}){\mathrm{\υ}}_{j,m}(t+\mathrm{\τ})={\mathrm{\ρ}}_{0}V\left(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)\right)\end{array}\right.$ Calculate next interior wagon flow transport information of interior each grid of two-dimentional road network constantly, wherein (x, y t) represent t (x, the y) density of position wagon flow, v (x, y, t) the expression t moment (x, the y) speed of position wagon flow, ρ constantly to ρ ₀Be the average density of current highway section wagon flow, ρ _{J, m}(t) and υ _{J, m}(t) the two-dimentional road network interior nodes of expression (j, density of m) locating and speed, (j _{Front_l}, m _{Front_l}) be that (j, m) along l the node in wagon flow direction the place ahead, τ is time delay, β _lBe weighting function, V is the optimal speed function, and n is a constant, and expression the place ahead provides the interstitial content of information;

The update displayed module, according to described next constantly in two-dimentional road network the wagon flow transport information in each grid upgrade the state of vehicle in the described two-dimentional road network, and it is presented in the three-dimensional scenic;

The timing simulation module repeats model computation module and update displayed module to carry out the timing simulation of wagon flow behavior.

6. the simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 5 is characterized in that, and is described

In the two dimension macroscopic flow model:

$V(\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right),{\mathrm{\ρ}}_0)=\frac{v_{\max }}{2}[\tanh (\frac{2}{{\mathrm{\ρ}}_0}-\frac{\underset{l=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\β}}_l{\mathrm{\ρ}}_{j_{\mathrm{front}\_l},m_{\mathrm{front}\_l}}\left(t\right)}{{\mathrm{\ρ}}_0^2}-\frac{1}{{\mathrm{\ρ}}_c})+\tanh \left(\frac{1}{{\mathrm{\ρ}}_c}\right)]$

ρ wherein _cBe the inverse of safe distance between vehicles, v _MaxBe the maximum speed limit in current highway section, tanh is a hyperbolic tangent function.

7. the simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 5 is characterized in that, if there is extraneous wagon flow to flow into current described two-dimentional road network, is translated into boundary condition treatment.

8. the simulation system based on the extensive traffic flow behavior of two-dimentional macroscopic flow model description as claimed in claim 6 is characterized in that,

The n value is 3, ${\mathrm{\β}}_l=\left\{\begin{array}{cc}2/3^l& l\≠3\\ l/3^{l-1}& l=3\end{array}\right.,$ L=0 wherein, 1,2,3, ρ _cValue 0.2vel./m, v _MaxValue is the desired speed of vehicle.

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