Kurzfristprognosen von Verkehrszuständen auf Basis von Verfahren der Mustererkennung und von dynamischen Routensuch- und Umlegungsverfahren
type: CreativeWork
description: Increasing traffic congestion (especially in areas of conurbation), the shortening of financial resources, and increasing resistance to further expansion of road networks, force consideration of more efficient usage of existing traffic infrastructure. This task requires an efficient traffic management system with intelligent traffic control measures and information for drivers. This also requires systems for the monitoring and prediction of traffic flow that can provide anticipatory and net-wide information about traffic states. In urban road networks, traffic states can only be measured directly on a limited number of network links. This is due to the limited density of traffic detection devices. For a large part of the network links traffic states have to be estimated. Thus, a net-wide prediction requires, in addition to a temporal extrapolation (prognosis), a spatial extrapolation of measured traffic states. An analysis of available approaches and methods for net-wide prediction of traffic states shows that no general methods are currently available that can solve the problem of spatial and temporal extrapolation of locally measured traffic states, in real-time, for large urban road networks. The integration of traffic assignment and traffic simulation models allows the estimating of traffic states, on network elements, using historical and actual measured data. Due to the capability of assignment and/or simulation models to estimate net-wide traffic states, this group of models is especially suitable for area-wide traffic estimating and prediction. The aim of this thesis is to develop a concept for a prediction system based on an iterative and dynamic traffic assignment procedure. This procedure is to be used as a tool for net-wide reconstruction of actual traffic states and for prediction of future traffic states. The iteration of a dynamic macroscopic route choice and traffic assignment procedure on the one hand, and the adjustment of the traffic demand inform…
abstract: Increasing traffic congestion (especially in areas of conurbation), the shortening of financial resources, and increasing resistance to further expansion of road networks, force consideration of more efficient usage of existing traffic infrastructure. This task requires an efficient traffic management system with intelligent traffic control measures and information for drivers. This also requires systems for the monitoring and prediction of traffic flow that can provide anticipatory and net-wide information about traffic states. In urban road networks, traffic states can only be measured directly on a limited number of network links. This is due to the limited density of traffic detection devices. For a large part of the network links traffic states have to be estimated. Thus, a net-wide prediction requires, in addition to a temporal extrapolation (prognosis), a spatial extrapolation of measured traffic states. An analysis of available approaches and methods for net-wide prediction of traffic states shows that no general methods are currently available that can solve the problem of spatial and temporal extrapolation of locally measured traffic states, in real-time, for large urban road networks. The integration of traffic assignment and traffic simulation models allows the estimating of traffic states, on network elements, using historical and actual measured data. Due to the capability of assignment and/or simulation models to estimate net-wide traffic states, this group of models is especially suitable for area-wide traffic estimating and prediction. The aim of this thesis is to develop a concept for a prediction system based on an iterative and dynamic traffic assignment procedure. This procedure is to be used as a tool for net-wide reconstruction of actual traffic states and for prediction of future traffic states. The iteration of a dynamic macroscopic route choice and traffic assignment procedure on the one hand, and the adjustment of the traffic demand inform…
author: von der Ruhren, Stefan
language: ger
keywords: info:eu-repo/classification/ddc/620, Ingenieurwissenschaften, Verkehrsmodell, Verkehrstechnik, Mustererkennung, Verkehrsleitsystem, Verkehrsmanagement, Kurzfristprognose, dynamische Routensuche und Umlegung, traffic model, pattern recognition, traffic management, short term prediction, dynamic traffic assignment
date published: 2006
date modified: 2026-07-30T19:43:10Z
provider: RWTH Aachen University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Publikationsserver der RWTH Aachen University