Doctoral Dissertations

Date of Award

12-1999

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Civil Engineering

Major Professor

Steve Richards

Committee Members

Arun Chatterjee, John Hungerford, Fred Wegmann

Abstract

As urban traffic continues to increase in metropolitan cities around the globe, transportation engineers are constantly attempting to improve the utilization of existent transportation systems. Their objective is to achieve maximum efficiency of these systems, in terms of movement of persons, services, and goods in a safe and convenient manner. Although congestion problems have existed in some major cities for some time, it has become a significant issue until recent years. The substantial increase in automobile ownership to meet our changing lifestyles in the last few decades, coupled with a decline of new highway construction, has stretched many roadway networks beyond their design capacity. To evaluate different traffic management strategies and their effect on the behavior of an urban street system is a very complex process due to the interrelationships between its components. Therefore, engineers have to rely on mathematical, computer-based simulation models to accurately predict the behavior of the system over a period of time. One of the most effective tools of traffic management is the application of computer simulation models to represent the traffic system, in order to determine the effects of traffic management strategies on the system's operational performance. This performance can be stated in terms of Measures of Effectiveness (MOE) on specific traffic parameters such as average vehicle speed, average travel time, vehicle stops, maximum queue length and fuel consumption. These MOE's can provide the traffic engineer with valuable insight into the responsiveness of the traffic stream to different operational strategies.

Among the many computer simulation programs, the TRAF-NETSIM, an Integrated Traffic Network Simulation model, is probably one of the most widely used and accepted traffic simulation models in The United States of America. TRAF-NETSIM is a very complex microscopic simulation model, which simulates the individual car movements stochastically. This research used TRAF-NETSIM Version 5.0 to determine the applicability and adaptability of this model to assess the traffic performance in Amman - Jordan, which was accomplished by the following steps:

  • A typical street network in Amman - Jordan, was selected and all the required input information to run NETSIM was collected from the field (The Test Network).
  • Two Measures of Effectiveness, Travel Time and Route Delay Time, were measured concurrently during the collection of traffic related input data.
  • The Test Network was used to collect the following traffic parameters needed to calibrate the NETSIM model.
    • Mean Start-Up Lost Time
      • Mean Queue Discharge Headway
    • Distribution of Start-Up Lost Time
    • Distribution of Queue Discharge Headway
  • Calibration on TRAF-NETSIM, in which the simulated results were compared with the observed field values using both the default and calibrated parameters.
  • A second street was selected in the same city to test the performance of the calibrated model (The Validation Network).

It was found that the TRAF-NETSIM model using the default traffic parameters did not adequately predict the traffic performance in the test network. However, after changing the embedded default parameters in TRAF-NETSIM with the measured values in the field, the simulated travel times and delay times, for weekdays other than Fridays, were similar to those observed for both street networks. Conversely, for Friday the model did not predict the measured travel time and delay time within a given accuracy for both the test and validation networks. It should be brought to the reader's attention that Friday is a holiday in Jordan and that the traffic on Friday is synonymous to Sunday traffic found in the United States of America.

Download
Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS