Traffic operations, traffic control devices, protected permitted signals, fya signals, signalized intersections, left turns, synchro


The Flashing Yellow Arrow Left Turn signal is quickly becoming prominent in Central Florida as a new method of handling left turns at traffic signals. While the concept of a protected-permitted left turn is not groundbreaking, the departure from the typical display of a five-section signal head is, for this type of operation. The signal head introduced is a four-section head with a flashing yellow arrow between the yellow and green arrows. With this signal head quickly becoming the standard, there is a need to re-evaluate the operational characteristics of the left turning vehicle and advance the knowledge of the significant parameters that may affect the ability for a driver to make a left turn at a signalized intersection. With previous research into the behavioral and operational characteristics of the flashing yellow arrow conducted, there is more information becoming available about the differences between this signal and the previously accepted method of allowing left turns at an intersection. The protected-permitted signal is typically displayed at an intersection with up to two through lanes and generally a protected signal is installed when the number of through lanes increases above two unless specific criteria is met. With the advent of larger arterials and more traffic on the highway networks, the push to operate these intersections at their maximum efficiency has resulted in more of these protected-permitted signals being present at these larger intersections, including the flashing yellow arrow. The core of the research that follows is a comparative analysis of the operation and parameters that affect the left turn movement of the intersection with larger geometry to that of the smaller geometry. The significant parameters of the left turn movement were examined through means of collecting, organizing and analyzing just over 68 hours of field data. This research details the determining of the significant parameters based on the generation of a simulation model of the protected left turn using Synchro, a traffic simulation package, and regression models using field driven data to determine the significant parameters for predicting the number of left turns that can be made in the permitted phase under specific operating conditions. Intuitively, there is an expectation that a larger intersection will not allow for as many permitted lefts as a smaller intersection with all conditions remaining the same. The conclusions drawn from this analysis provide the framework to understanding the similarities and the differences that are encountered when the intersection geometry differs and help to more efficiently manage traffic at signalized intersections. The work of this field promises to enhance the operations of the left turning movement for traffic control devices. With an understanding of the statistical models generated, a broader base of knowledge is gained as to the significant parameters that affect a driver's ability to make the left turn. A discussion of the statistical differences and between the models generated from the small and large geometry intersections is critical to drive further research into standards being developed for the highway transportation network and the treatment of these large signalized intersections. The exploration of specific parameters to predict the number of permitted left turns will yield results as to if there is more to be considered with larger intersections moving forward as they become a standard sight on the roadway network.


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Graduation Date





Radwan, Essam A.


Master of Science (M.S.)


College of Engineering and Computer Science


Civil, Environmental, and Construction Engineering

Degree Program

Civil Engineering; Transportation System Engineering








Release Date

August 2014

Length of Campus-only Access


Access Status

Masters Thesis (Open Access)


Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic