Characteristics and Initial Density Distribution in Traffic Flow Wave Equation

In summary, the conversation discusses a stretch of highway where the net flow of cars entering is constant, and the governing equation of motion is given by a partial differential equation. The variation of the initial density distribution is shown to be a function of time and the initial density at a certain point. The conversation also touches upon the use of Mathematica to graph the space-time diagram, but it is unclear how to do so without specific values for the constants involved.
  • #1
Dustinsfl
2,281
5
Suppose that along a stretch of highway the net flow of cars entering (per unit length) can be taken as a constant $\beta_0$.
The governing equation of motion is then
$$
\frac{\partial\rho}{\partial t} + c(\rho)\frac{\partial\rho}{\partial x} = \beta_0
$$
where
$$
c(\rho) = u_{\text{max}}\left(1 - \frac{2\rho}{\rho_{\text{max}}}\right).
$$
Show that the variation of the initial density distribution is given by
$$
\rho = \beta_0t + \rho(x_0,0)
$$
along a characteristic emanating from $x = x_0$ described by
$$
x = x_0 + u_{\text{max}}\left(1 - \frac{2\rho(x_0,0)}{\rho_{\text{max}}}\right)t - \beta_0\frac{u_{\text{max}}}{\rho_{\text{max}}}t.
$$

What I have done so far is:
$\frac{dt}{dr} = 1\Rightarrow t = r + c$ but when $t = 0$, we have $t = r$.

$\frac{dx}{dr} = c(\rho)\Rightarrow x = tu_{\text{max}}\left(1-\frac{2\rho}{\rho_{\text{max}}}\right)+c$ but when $t=0$, we have
$$
x = tu_{\text{max}}\left(1-\frac{2\rho}{\rho_{\text{max}}}\right) + x_0.
$$

$\frac{d\rho}{dr} = \beta_0\Rightarrow \rho = t\beta_0 + c$

How do I get to
$$
\rho(x,t) = t\beta_0 +\rho(x_0,0)
$$
and their characteristic?
 
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  • #2
Hi dwsmith, :)

dwsmith said:
$\frac{d\rho}{dr} = \beta_0\Rightarrow \rho = t\beta_0 + c$

How do I get to
$$
\rho(x,t) = t\beta_0 +\rho(x_0,0)
$$
and their characteristic?

\[\rho = t\beta_0 + c\]

When, \(t=0\) we have, \(\rho(x=x_{0},t=0)=\rho(x_{0},0)\). Therefore,

\[\rho=t\beta_{0}+\rho(x_{0},0)\]

dwsmith said:
$\frac{dx}{dr} = c(\rho)\Rightarrow x = tu_{\text{max}}\left(1-\frac{2\rho}{\rho_{\text{max}}}\right)+c$ but when $t=0$, we have
$$
x = tu_{\text{max}}\left(1-\frac{2\rho}{\rho_{\text{max}}}\right) + x_0.
$$

This is incorrect. Note that \(\rho\) depends on \(t\) but you have considered it as a constant when integrating. The correct method is to substitute for \(\rho\) first so as to obtain,

\[\frac{dx}{dr}=\frac{dx}{dt}=c(\rho)=u_{\text{max}}\left(1 - \frac{2\rho}{\rho_{\text{max}}}\right)\]

\[\Rightarrow \frac{dx}{dt}=u_{\text{max}}\left(1 - \frac{2\rho(x_{0},0)}{\rho_{\text{max}}}\right)-\frac{2\beta_{0}u_{\text{max}}t}{\rho_{\text{max}}}\]

Integration gives,

\[x=x_{0}+u_{\text{max}}\left(1 - \frac{2\rho(x_{0},0)}{\rho_{\text{max}}}\right)t-\frac{\beta_{0}u_{\text{max}}t^{\color{red}2}}{ \rho_{\text{max}}}\]

Kind Regards,
Sudharaka.
 
  • #3
Sudharaka said:
\[\Rightarrow \frac{dx}{dt}=u_{\text{max}}\left(1 - \frac{2\rho(x_{0},0)}{\rho_{\text{max}}}\right)-\frac{2\beta_{0}u_{\text{max}}t}{\rho_{\text{max}}}\]

Where did this piece come from?

$$\frac{2\beta_{0}u_{\text{max}}t}{\rho_{\text{max}}}$$
 
  • #4
dwsmith said:
Where did this piece come from?

$$\frac{2\beta_{0}u_{\text{max}}t}{\rho_{\text{max}}}$$

Substitute \(\rho=t\beta_{0}+\rho(x_{0},0)\) for \(\rho\) in \(\frac{dx}{dt}=c(\rho)=u_{\text{max}} \left(1 - \frac{2\rho}{\rho_{\text{max}}}\right)\)
 
  • #5
Sudharaka said:
Substitute \(\rho=t\beta_{0}+\rho(x_{0},0)\) for \(\rho\) in \(\frac{dx}{dt}=c(\rho)=u_{\text{max}} \left(1 - \frac{2\rho}{\rho_{\text{max}}}\right)\)

How can I use Mathematica to sketch the space time diagram?
 
  • #6
dwsmith said:
How can I use Mathematica to sketch the space time diagram?

I have never used Mathematica so I won't be able to answer your question. By space-time diagram do you mean the graph between \(x\) and \(t\) ?
 
  • #7
Sudharaka said:
I have never used Mathematica so I won't be able to answer your question. By space-time diagram do you mean the graph between \(x\) and \(t\) ?

Yes
 
  • #8
dwsmith said:
Yes

In that case it is a parabola. But do you have any specific values for the constants, \(x_{0},\,u_{\text{max}},\,\rho(x_{0},0),\,\rho_{ \text{max}}\mbox{ and }\beta_{0}\) ?
 
  • #9
Sudharaka said:
In that case it is a parabola. But do you have any specific values for the constants, \(x_{0},\,u_{\text{max}},\,\rho(x_{0},0),\,\rho_{ \text{max}}\mbox{ and }\beta_{0}\) ?
No.
 
  • #10
dwsmith said:
No.

Then it seems problematic as to how you would graph this equation in any mathematical software. What you can only say is that the graph between \(x\) and \(t\) is parabolic.
 

FAQ: Characteristics and Initial Density Distribution in Traffic Flow Wave Equation

What is the traffic flow wave equation?

The traffic flow wave equation is a mathematical model that describes the propagation of traffic congestion in a roadway network. It takes into account factors such as vehicle density, speed, and flow to predict the formation and dissipation of traffic jams.

How is the traffic flow wave equation used?

The traffic flow wave equation is used by traffic engineers and transportation planners to design and manage roadways. It can also be used to develop traffic control strategies and improve traffic flow.

What factors affect the traffic flow wave equation?

The traffic flow wave equation is affected by several factors including roadway geometry, traffic signal timing, vehicle characteristics, and driver behavior. Changes in any of these factors can impact traffic flow and the formation of congestion.

Can the traffic flow wave equation accurately predict traffic patterns?

The traffic flow wave equation is a simplification of real-world traffic conditions and cannot accurately predict every traffic situation. However, it can provide useful insights and help inform decision-making in transportation planning.

How can the traffic flow wave equation be improved?

Researchers and scientists are constantly working to improve the traffic flow wave equation by incorporating more advanced models and data. This includes factors such as real-time traffic data, weather conditions, and human behavior to create more accurate predictions and improve traffic management strategies.

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