Thesis (Ph.D.)--University of Texas at Arlington, 2009.

Thesis (Ph.D.)--University of Texas at Arlington, 2009.

Thesis (M.S. in Civil and Environmental Engineering)--University of California, Davis, 2007. / Text document in PDF format. Title from PDF title page (viewed on August 28, 2009). "Received by ITS-Davis: November 2007"--Publication detail webpage. Includes bibliographical references (p. 110-115).

This thesis presents a statistical analysis of weaving in a managed lane system which is evolving from a High-Occupancy Vehicle (HOV) system to a High-Occupancy Toll system (HOT). Weaving was, assessed along the I-85 corridor in Atlanta, during three different phases in the conversion from HOV to HOT: 1) the existing HOV managed lane system prior to conversion to HOT lanes, 2) after restriping of some weaving zones but prior to conversion of the HOV lanes to HOT lanes and, 3) after the HOT managed lane system opened. Each phase was analyzed to see how weaving behavior into and out of the managed lane system was affected by changes in the system. To accomplish the analysis, video was collected using Georgia Department of Transportation cameras along the corridor. The videos were transferred to an Android Tablet, in which an App developed by the research team was used to record data from the videos. Using the processed weaving data, a comparison of weaving activity during each phase was performed. Data were also analyzed across time of day, speed differentials, and whether the weaves in question were performed legally (within established weaving zones) or illegally (across double-solid striped lane markings). After a comparison of weaving behavior along different variables, a regression tree analysis was completed. The analysis showed that weaving intensity increased as the system was converted from HOV to HOT. However, illegal weaving decreased significantly once the HOT system was in place, perhaps due to stricter enforcement or perhaps due to driver response to illegally entering and leaving tolled lanes. The regression tree analyses indicated that weaving intensity was highly dependent upon whether it was legal or illegal to weave and upon the phase of conversion during which the weave occurred.

A 15.5-mile portion of the I-85 high-occupancy vehicle (HOV) lane in the metropolitan area of Atlanta, GA was converted to a high-occupancy toll (HOT) lane as part of a federal demonstration project designed to provide a reliable travel option through this congested corridor. Results from the I-85 demonstration project provided insight into the results that may follow the Georgia Department of Transportation's planned implementation of a $16 billion HOT lane network along metropolitan Atlanta's other major roadways [2]. To evaluate the impacts of the conversion, it was necessary to measure changes in corridor travel speed, reliability, vehicle throughput, passenger throughput, lane weaving, and user demographics. To measure such performance, a monitoring project, led by the Georgia Institute of Technology collected various forms of data through on-site field deployments, GDOT video, and cooperation from the State Road and Toll Authority (SRTA). Changes in the HOT lane's speed, reliability or other performance measure can affect the demographic and vehicle characteristics of those who utilize the corridor. The purpose of this particular study was to analyze the changes to the vehicle characteristics by comparing vehicle occupancy, vehicle classifications, and vehicle registration data to their counterparts from before the HOV-to-HOT conversion. As part of the monitoring project, the Georgia Tech research team organized a two-year deployment effort to collect data along the corridor during morning and afternoon peak hours. One year of data collection occurred before the conversion date to establish a control and a basis from which to compare any changes. The second year of data collection occurred after the conversion to track those changes and observe the progress of the lane's performance. While on-site, researchers collected data elements including visually-observed vehicle occupancy, license plate numbers, and vehicle classification [25]. The research team obtained vehicle records by submitting the license plate tag entries to a registration database [26]. In previous work, vehicle occupancy data were collected independently of license plate records used to establish the commuter shed. For the analyses reported in this thesis, license plate data and occupancy data were collected concurrently, providing a link between occupancy records of specific vehicles and relevant demographic characteristics based upon census data. The vehicle records also provided characteristics of the users' vehicles (light-duty vehicle vs. sport utility vehicle, model year, etc.) that the researchers aggregated to identify general trends in fleet characteristics. The analysis reported in this thesis focuses on identifying changes in vehicle characteristics that resulted from the HOV-to-HOT conversion. The data collected from post-conversion are compared to pre-conversion data, revealing changes in vehicle characteristics and occupancy distributions that most likely resulted from the implementation of the HOT lane. Plausible reasons affecting the vehicle characteristics alterations will be identified and further demographic research will enhance the data currently available to better pinpoint the cause and effect relationship between implementation and the current status of the I-85 corridor. Preliminary data collection outliers were identified by using vehicle occupancy data. However, future analysis will reveal the degree of their impact on the project as a whole. Matched occupancy and license plate data revealed vehicle characteristics for HOT lane users as well as indications that the tested data collectors are predominantly synchronized when concurrently collecting data, resulting in an argument to uphold the validity of the data collection methods. Chapter two provides reasons for why HOT lanes were sought out to replace I-85's HOV lanes. Chapter two will also provide many details regarding how the HOT lanes function and it will describe the role the Georgia Institute of Technology played in the assessment the HOV-to-HOT conversion. Chapter three includes the methodologies used to complete this document while chapter four provides results and analysis for the one year period before the conversion and the one year period after the conversion.