Khattak, Zulqarnain Habib
(2016)
Evaluating the Operational and Safety Aspects of Adaptive Traffic Control Systems in Pennsylvania.
Master's Thesis, University of Pittsburgh.
(Unpublished)
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PDF (EVALUATING THE OPERATIONAL & SAFETY ASPECTS OF ADAPTIVE TRAFFIC CONTROL SYSTEMS IN PENNSYLVANIA)
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Abstract
Adaptive Signal Control Technology (ASCT) is a novel Intelligent Traffic System (ITS) technology developed to optimize cycle lengths, green times or phasing sequences for traffic signals based on the changing traffic volumes collected from advanced detectors. While ASCT are considered to improve mobility and reduce congestion, they also have the potential to reduce crashes and improve traffic safety.
This research explored these potential safety benefits of adaptive signal control systems through a two-step process. During the first stage, a 22 intersection corridor on Center Ave and Baum Boulevard, recently deployed with SURTRAC adaptive signals was selected and travel time runs were conducted with and without SURTRAC in operation using a GPS mobile app known as GPS tracks. The results did provide indications for safety benefits through reduced stops made along the intersections and improvement in travel time.
During the second stage of the research project, 41 urban/suburban intersections from the state of Pennsylvania with SURTRAC and In-Sync ASCT deployments were selected and evaluated for their safety benefits using the Empirical Bayes (EB) before and after predictive method. National Safety Performance Functions (SPF) were selected for total and fatal & injury crash categories to calculate expected average crash frequencies for the selected intersections. The calculated expected average crash frequencies were used along with the observed crash frequencies from Pennsylvania Department of Transportation (PennDOT) crash reports in the rigorous EB method to calculate crash modification factors for adaptive signal control system. The findings, which evaluated a correlation based upon the development of Crash Modification Factor (CMF) proved the potential of ASCT to reduce crashes and improve traffic safety since the CMF values for total and fatal & injury crashes for both of the systems (SURTRAC & In-Sync) showed a significant correlation. Deploying ASCT was found to reduce total crashes by 34% with a CMF value of 0.66 and fatal & injury crashes by 45% with a CMF value of 0.55. CMF=1 means no change in safety conditions and CMF<1 indicates a reduction in crashes. The CMF correlations were found to be statistically significant at a 95% confidence level. The research findings will enable engineers and professionals to predict the potential reduction in crashes that would be expected after deploying ASCT at any new intersection.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
14 June 2016 |
| Date Type: |
Publication |
| Defense Date: |
25 March 2016 |
| Approval Date: |
14 June 2016 |
| Submission Date: |
3 March 2016 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
99 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Civil and Environmental Engineering |
| Degree: |
MSCE - Master of Science in Civil Engineering |
| Thesis Type: |
Master's Thesis |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Adaptive traffic control, Empirical Bayes, Traffic safety, GPS Tracks |
| Date Deposited: |
14 Jun 2016 18:06 |
| Last Modified: |
15 Nov 2016 14:31 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/26899 |
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