Thesis (MTech (Civil Engineering))--Cape Peninsula University of Technology, 2008. / Includes bibliographical references (leaves 91-94). Also available online.

University of Macau / Faculty of Science and Technology / Department of Civil and Environmental Engineering

No description available.

The main objective of this research is to develop a model to predict congestion. This model is developed using the techniques of simulation and as the model requires dynamic modeling, DYNAMO is used. This model incorporates the three-regime linear model for establishing a relationship between speed and density of the traffic stream. The input to this model is obtained from a presence type detector system. These measurements are then used to calculate various parameters and then the state of the traffic flow for the vehicular stream in the test zone is determined. This model also predicts the state of the traffic stream in any other section of the highway behind the test section. The model developed is flexible and easy to incorporate in any traffic control system. This research is also intended to simulate the various traffic stream models and evaluate their performance regarding their capability to represent highway traffic flow conditions. A thorough review of the fundamentals of traffic flow is required to achieve these objectives. The simulation models developed for these traffic stream formulae incorporate various measures of effectiveness to determine congestion. These measures of effectiveness are used to define congestion. The study of the various traffic stream models is necessary in order to develop a flexible and efficient model to predict congestion. The congestion prediction model developed incorporates all the parameters required to define congestion. / Master of Science

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

published_or_final_version / Transport Policy and Planning / Master / Master of Arts

published_or_final_version / Geography and Geology / Master / Master of Philosophy

M. Tech. (Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology / Traffic congestion is a concern within the main arteries that link Johannesburg to Pretoria. In this study Matlab function Randperm is used to generate random vehicle speeds on a simulated highway. Randperm is used to mimic vehicle speed sensors capturing vehicle traffic on the highway. Java sockets are used to send vehicle speed to the Road Traffic Control Centre (RTCC)-database server through a wireless medium. The RTCC-database server uses MySQL to store vehicle speed data. The domain controller with active directory together with a certificate server is used to manage and provide security access control to network resources. The wireless link used by speed sensors to transmit vehicle speed data is protected using PEAP with EAP-TLS which employs the use of digital certificates during authentication. A java database connectivity driver is used to retrieve data from MySQL and a multilayer perceptron (MLP) model is used to predict future traffic status on the highway being monitored i.e. next 5 minutes from previous 5 minutes captured data. A dataset of 402 instances was divided as follows: 66 percent training data was used to train the MLP model, 15 percent data used during validation and the remaining 19 percent was used to test the trained MLP model. An excel spreadsheet was used to introduce novel (19 percent data not used during training) data to the trained MLP model to predict. Assuming that the spreadsheet data represent captured highway vehicle data for the last 5 minutes, the model showed 100 percent accuracy in predicting the four classes: congested, out congested, into congested and normal traffic flow. Predicted traffic status is displayed for the motorist on the highway to know. Ability of the proposed model to continuously capture the traffic pattern on the highway (monitor) helps in redirecting (controlling) the highway traffic during periods of congestion. Implementation of this project will definitely decrease traffic congestion across main arteries of Johannesburg. Pollution normally experienced when cars idle for a long time during congestion will be reduced by free highway traffic flow. Frequent servicing of motor vehicles will no longer be required by the motorists. Furthermore the economy of Gauteng and South Africa as a whole will benefit due to increase in production. Consumers will also benefit in obtaining competitive prices from organizations that depend on haulage services.

As transportation policies are changing to encourage alternative modes of transportation to reduce congestion problems and air quality impacts, more planning organizations are considering or implementing activity-based travel demand models to forecast future travel patterns. The proclivity towards operating activity-based models is the capability to model disaggregate travel data to better understand the model results that are generated with respect to the latest transportation policy implementations. This thesis first examines the differences between the two major modeling techniques used in the United States and then describes the assessment tool that was developed to recommend whether a region should convert to the advanced modeling procedures. This tool consists of parameters that were decided upon based on their known linkages to the advantages of activity-based models.

published_or_final_version / Public Administration / Master / Master of Public Administration