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esis_ug/ext/KreuzungA12.pdf>] [29] [30 <C:/Daten/source/college/ss2013/Bachelor
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helor Thesis/thesis_ug/ext/KreuzungA29.pdf>] [32 <C:/Daten/source/college/ss201
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3/Bachelor Thesis/thesis_ug/ext/KreuzungA46.pdf>] [33] [34 <C:/Daten/source/col
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lege/ss2013/Bachelor Thesis/thesis_ug/ext/KreuzungA104.pdf>]
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@ -10,35 +10,36 @@
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\contentsline {subsection}{\numberline {5.3}Modell als Matrix}{9}
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\contentsline {subsubsection}{\numberline {5.3.1}Verbindungsmatrizen}{9}
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\contentsline {subsubsection}{\numberline {5.3.2}Berechnungsmatrizen}{9}
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\contentsline {section}{\numberline {6}Daten}{10}
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\contentsline {subsection}{\numberline {6.1}Induktionsschleifenwerte}{10}
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\contentsline {subsubsection}{\numberline {6.1.1}CSV-Daten der Stadt Darmstadt}{10}
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\contentsline {subsubsection}{\numberline {6.1.2}Mysql-Daten des Projektes Verkehrsvisualisierung}{11}
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\contentsline {subsection}{\numberline {6.2}CAD-Zeichnungen der Kreuzungen}{11}
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\contentsline {subsection}{\numberline {6.3}Abbiegewahrscheinlichkeiten}{11}
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\contentsline {subsubsection}{\numberline {6.3.1}Abbiegewahrscheinlichkeiten der Stadt Darmstadt}{11}
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\contentsline {subsubsection}{\numberline {6.3.2}Abbiegewahrscheinlichkeiten von Michael Scholz}{11}
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\contentsline {subsection}{\numberline {6.4}Aufbereitung der Daten}{11}
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\contentsline {subsubsection}{\numberline {6.4.1}Datenbank Schema}{12}
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\contentsline {subsubsection}{\numberline {6.4.2}Aufbereiten der Induktionsschleifenwerte}{12}
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\contentsline {subsubsection}{\numberline {6.4.3}Aufbereiten der Abbiegewahscheinlichkeiten}{12}
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\contentsline {subsubsection}{\numberline {6.4.4}Geographischer Ausschnitt der Daten}{12}
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\contentsline {section}{\numberline {7}Berechnung}{14}
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\contentsline {subsection}{\numberline {7.1}Das Zeitproblem}{14}
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\contentsline {subsection}{\numberline {7.2}Ans\"atze}{14}
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\contentsline {subsubsection}{\numberline {7.2.1}Markov-Ketten HMM}{14}
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\contentsline {subsubsection}{\numberline {7.2.2}Neuronale Netze}{14}
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\contentsline {subsubsection}{\numberline {7.2.3}Gleichungssystem}{14}
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\contentsline {subsection}{\numberline {7.3}Lineares Gleichungssystem}{14}
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\contentsline {subsubsection}{\numberline {7.3.1}Gleichungen innerhalb einer Kreuzung}{14}
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\contentsline {subsubsection}{\numberline {7.3.2}Gleichungen zwischen Kreuzungen}{14}
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\contentsline {subsection}{\numberline {7.4}Lineares Gleichungssystem als Graph}{14}
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\contentsline {section}{\numberline {8}Visualisierung}{15}
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\contentsline {subsection}{\numberline {8.1}Visualisierung des Graphen mit Geoinformationen}{15}
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\contentsline {subsection}{\numberline {8.2}Visualisierung des JGraphT-Graphen}{15}
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\contentsline {section}{\numberline {9}Validierung}{16}
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\contentsline {subsection}{\numberline {9.1}Testdatenmenge}{16}
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\contentsline {subsection}{\numberline {9.2}Verkehrszählung}{16}
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\contentsline {subsection}{\numberline {9.3}Validierung der Verkehrsaufkommensvorhersage}{16}
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\contentsline {section}{\numberline {10}Ausblick}{17}
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\contentsline {section}{\numberline {11}Anhang}{19}
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\contentsline {section}{\numberline {6}Daten}{11}
|
||||
\contentsline {subsection}{\numberline {6.1}Induktionsschleifenwerte}{11}
|
||||
\contentsline {subsubsection}{\numberline {6.1.1}CSV-Daten der Stadt Darmstadt}{11}
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\contentsline {subsubsection}{\numberline {6.1.2}Mysql-Daten des Projektes Verkehrsvisualisierung}{12}
|
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\contentsline {subsection}{\numberline {6.2}CAD-Zeichnungen der Kreuzungen}{12}
|
||||
\contentsline {subsection}{\numberline {6.3}Abbiegewahrscheinlichkeiten}{12}
|
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\contentsline {subsubsection}{\numberline {6.3.1}Abbiegewahrscheinlichkeiten der Stadt Darmstadt}{12}
|
||||
\contentsline {subsubsection}{\numberline {6.3.2}Abbiegewahrscheinlichkeiten von Michael Scholz}{12}
|
||||
\contentsline {subsection}{\numberline {6.4}Aufbereitung der Daten}{12}
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\contentsline {subsubsection}{\numberline {6.4.1}Datenbank Schema}{13}
|
||||
\contentsline {subsubsection}{\numberline {6.4.2}Aufbereiten der Induktionsschleifenwerte}{13}
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||||
\contentsline {subsubsection}{\numberline {6.4.3}Aufbereiten der Abbiegewahscheinlichkeiten}{13}
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\contentsline {subsubsection}{\numberline {6.4.4}Geographischer Ausschnitt der Daten}{13}
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\contentsline {section}{\numberline {7}Berechnung}{15}
|
||||
\contentsline {subsection}{\numberline {7.1}Das Zeitproblem}{15}
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\contentsline {subsection}{\numberline {7.2}Ans\"atze}{15}
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\contentsline {subsubsection}{\numberline {7.2.1}Markov-Ketten HMM}{15}
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\contentsline {subsubsection}{\numberline {7.2.2}Neuronale Netze}{15}
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||||
\contentsline {subsubsection}{\numberline {7.2.3}Gleichungssystem}{15}
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\contentsline {subsubsection}{\numberline {7.2.4}Wegfindungsalgorithmen}{15}
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\contentsline {subsection}{\numberline {7.3}Lineares Gleichungssystem}{15}
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\contentsline {subsubsection}{\numberline {7.3.1}Lineares Gleichungssystem einer Kreuzung}{15}
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\contentsline {subsubsection}{\numberline {7.3.2}Gleichungen zwischen Kreuzungen}{15}
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\contentsline {subsection}{\numberline {7.4}Lineares Gleichungssystem als Graph}{16}
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\contentsline {section}{\numberline {8}Visualisierung}{17}
|
||||
\contentsline {subsection}{\numberline {8.1}Visualisierung des Graphen mit Geoinformationen}{17}
|
||||
\contentsline {subsection}{\numberline {8.2}Visualisierung des JGraphT-Graphen}{17}
|
||||
\contentsline {section}{\numberline {9}Validierung}{18}
|
||||
\contentsline {subsection}{\numberline {9.1}Testdatenmenge}{18}
|
||||
\contentsline {subsection}{\numberline {9.2}Verkehrszählung}{18}
|
||||
\contentsline {subsection}{\numberline {9.3}Validierung der Verkehrsaufkommensvorhersage}{18}
|
||||
\contentsline {section}{\numberline {10}Ausblick}{19}
|
||||
\contentsline {section}{\numberline {11}Anhang}{21}
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
In diesem Kapitel werden einige Berechnungsansätze beschrieben, sowie Probleme mit diesen Ansätzen. Außerdem werden Problemstellungen formuliert, welche sich teilweise als lösbar herausgestellt haben.
|
||||
|
||||
\subsection{Das Zeitproblem}{
|
||||
Die Daten sind zeitdeterministisch(?). Außerdem zeigen sie eine Momentaufnahme des geschehens. Das Hauptproblem ist, dass zwischen Kreuzungen keine Sensoren verbaut sind. Eine 'Verfolgung' eines Autos ist somit nicht möglich, da nicht festgestellt werden kann, wie weit es bis zur nächsten Momentaufnahme gekommen ist.
|
||||
|
||||
@ -16,14 +18,19 @@
|
||||
Neuronale Netze zum lernen der Abbiegewahrscheinlichkeit.
|
||||
}
|
||||
\subsubsection{Gleichungssystem}{
|
||||
Gehen wir von einem Geregelten, Verkehrsordnung achtenden Verkehr aus, können wir für jeden Ausgangsknoten durch addition derjenigen Sensorwerte, welche auf den Ausgang zeigen berechnen, wieviele Autos am Ausgangsknoten angekommen sind. Das Problem dabei sind die Mischspuren. Mischspuren bzw. Mischspurensensoren sind solche Straßenabschnitte, welche zwei mögliche Ausgänge bedienen können. Für diese Sensoren werden Abbiegewahrscheinlichkeiten benötigt. Der Sensorwert wird entsprechend mit der jeweiligen Abbiegewahrscheinlichkeit multipliziert und auf den Ausgang addiert.
|
||||
Gehen wir von einem Geregelten, Verkehrsordnung achtenden Verkehr aus, können wir für jeden Ausgangsknoten durch addition derjenigen Sensorwerte, welche auf den Ausgang zeigen berechnen, wieviele Autos am Ausgangsknoten angekommen sein müssen. Das Problem dabei sind die Mischspuren, über welche der Verkehr in verschiedene Richtungen fließen kann. Für diese Sensoren werden Abbiegewahrscheinlichkeiten benötigt um zu berechnen, wie viel Prozent der Autos, welche über den Sensor Fahren an dem jeweiligen Ausgangsknoten angelangen. Der Sensorwert wird entsprechend mit der jeweiligen Abbiegewahrscheinlichkeit multipliziert und auf den Ausgang addiert.\\
|
||||
|
||||
Da lineare Gleichungssysteme das Ergebnis dieser Arbeit sind ist ihnen ein eigenes Kapitel, um genauer darauf einzugehen.
|
||||
|
||||
}
|
||||
\subsubsection{Wegfindungsalgorithmen}{
|
||||
Auf einem Graphen bietet es sich an einen Wegfindungsalgorithmus zu verwenden, um Autos realistisch zu modellieren.
|
||||
Problem ist nur, dass keine Daten über das Ziel der Autos bekannt ist.
|
||||
}
|
||||
}
|
||||
\subsection{Lineares Gleichungssystem}{
|
||||
\subsubsection{Gleichungen innerhalb einer Kreuzung}{
|
||||
|
||||
|
||||
\subsubsection{Lineares Gleichungssystem einer Kreuzung}{
|
||||
Maxtrix * Sensorwertematrix = Ausgangsbelegung
|
||||
|
||||
Ausgang = A{K € e(K,Ausgang)| += k.count * e.abbiegewahrscheinlichkeit}
|
||||
@ -40,4 +47,4 @@
|
||||
Forward/Backward Iteration.
|
||||
}
|
||||
}
|
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+6
|
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+5
|
||||
@ -136,7 +136,11 @@ In dieser Arbeit wird eine Zweistufenmodellierung vorgestellt, welches für Kreu
|
||||
der Matrix verzeichnet, alle Sensoren dieser Kreuzung auf der Y-Achse.
|
||||
|
||||
Am Beispiel der Kreuzung A23 sei das hier demonstriert.
|
||||
[Kreuzungsbild]\\
|
||||
\begin{figure}[htbp!]
|
||||
\centering
|
||||
\fbox{\includegraphics[width=0.5\textwidth-2\fboxsep-2\fboxrule]{ext/KreuzungA23}}
|
||||
\caption{Kreuzung A23}
|
||||
\end{figure}
|
||||
$\begin{Bmatrix}
|
||||
& A1 & A2 & A3 & A4 \\
|
||||
S1 & 0 & 0 & 0 & 0 \\
|
||||
@ -184,4 +188,4 @@ In dieser Arbeit wird eine Zweistufenmodellierung vorgestellt, welches für Kreu
|
||||
}
|
||||
|
||||
}
|
||||
+3
|
||||
+2
|
||||
Loading…
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Reference in New Issue
Block a user