Development of a Queue Growth and Dissipation Model

Publication Date

7-2005

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Civil Engineering

Department

Civil Engineering

Major Advisor

Mandar Khanal

Abstract

The purpose of the research was to build a freeway queue growth and dissipation model in fulfillment of the thesis requirement for my Master of Science degree in Civil Engineering at Boise State University. The research involved developing a model that would predict queue growth and dissipation information for any two points on a freeway. A computer application for the model was developed in the research.

Because of traffic data availability and heavy traffic flows, a section of Interstate freeway 84 (I-84) between Boise and Meridian in Idaho was selected for the research. The section of I-84 selected for the study is between Cloverdale Road and Meridian Road.

The Treasure Valley Advanced Traffic Management System (A TMS) was the data resource in the research. The traffic data was recorded in real-time, every 30 seconds. The 30-second data can be aggregated to desired levels in the ATMS. The 15-minute cumulative traffic data was used in the research because it is more stable than 30-second data.

The objectives of the research were to (1) predict traffic queue growth and dissipation when traffic demand exceeds capacity, (2) calculate the expected travel time between two points on the freeway, and (3) build a computer application that implements the developed methodology.

The methods used for developing the queue growth and dissipation model were based on analytical methods and graphical analyses. I believe that the work presented here is the first ever application of these methods to real-time data.

The queue length and the travel time can be calculated using graphical analyses if the arriving traffic flow data and the capacity of the bottleneck are known. On freeways, a bottleneck is a restriction point where traffic demand exceeds the capacity. Bottlenecks are the key reasons for traffic queues. In the developed model, the results were calculated for every 15 minutes.

The model was built for two types of bottlenecks: permanent bottlenecks (for example, traffic lane drops) and temporary bottlenecks (for example, incidents). The queue growth and dissipation model was completed and implemented into a computer worksheet.

After the real-time incoming traffic flow data at the upstream of the bottleneck and the capacity of the bottleneck are entered, the developed queue analysis worksheet will automatically generate the real-time queue length and the travel time through the congested section. I chose the Meridian Road interchange on westbound I-84 as an example of a permanent bottleneck.

A Traffic Software Integrated System (TSIS) simulation model was built for the Meridian Road interchange to test the graphical analysis model. At the 5% significance level, the means of the predicted results are not significantly different for these two models. In addition, the developed model was verified with field data from the Meridian Road interchange. Comparison with the field data revealed that most of the test errors were found to be less than 20%. At the 5% significance level, the means of the predicted results are not significantly different from the field data.

The output of the queue analysis worksheet includes a report of the everyday queue length and the travel time in queue information at any two points on freeways. Knowledge of the queue length is important in applications, where the queue must be contained in order to avoid blocking upstream facilities. This information will be useful for traffic mangers, who are responsible for day-to-day operation of freeway systems. It will be especially useful for local managers from the Idaho Transportation Department (ITD) and the Ada County Highway District (ACHD).

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