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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Search results

Showing 1 to 3 of 3 (0.063 seconds)
1

Design of an Intelligent Traffic Management System

Azimian, Amin January 2011 (has links)
No description available.
Civil Engineering
Intelligent
traffic detectors
shortest path
travel time
mean speed
2

Centralizované vyhodnocování zátěže dopravního systému / Centralised Traffic System Load Evaluation

Zukal, Marek January 2010 (has links)
There are statistical data gathered as a part of the operation of the intersections controlled by the traffic light signalling devices. This data concerns characteristics of traffic flows and parameters of the aplied controlling strategy and can be valuable source of information that can be used to improve the controlling strategy or creation of a mathematical model describing the behaviour of the traffic flows. These models are closely studied and used for prediction of the immediate development of the traffic flows based on their current states. This paper is trying to design means to create such models and to work with them.
3

Travel time estimation in congested urban networks using point detectors data

Mahmoud, Anas Mohammad 02 May 2009 (has links)
A model for estimating travel time on short arterial links of congested urban networks, using currently available technology, is introduced in this thesis. The objective is to estimate travel time, with an acceptable level of accuracy for real-life traffic problems, such as congestion management and emergency evacuation. To achieve this research objective, various travel time estimation methods, including highway trajectories, multiple linear regression (MLR), artificial neural networks (ANN) and K –nearest neighbor (K-NN) were applied and tested on the same dataset. The results demonstrate that ANN and K-NN methods outperform linear methods by a significant margin, also, show particularly good performance in detecting congested intervals. To ensure the quality of the analysis results, set of procedures and algorithms based on traffic flow theory and test field information, were introduced to validate and clean the data used to build, train and test the different models.
Travel time
Congested Networks
Computer science
Artificial Intelligence
Intelligent Transportation systems
Neural Networks
point detectors
Multiple linear regression
Matlab
Estimation
K nearest neighbors
congestions
data cleaning
traffic detectors
emergency evacuation
GPS

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