Year

2019

Season

Fall

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Civil Engineering (MSCE)

Department

Engineering

NACO controlled Corporate Body

University of North Florida. School of Engineering

First Advisor

Dr. Thobias Sando

Second Advisor

Dr. Priyanka Alluri

Department Chair

Dr. Osama Jadaan

College Dean

Dr. William F. Klostermeyer

Abstract

The Adaptive Signal Control Technology (ASCT) is a traffic management strategy that optimizes signal timing based on real-time traffic demand. This thesis proposes a comprehensive methodology of quantifying the mobility and safety benefits of the ASCT deployed in the state of Florida. A Bayesian switch-point regression model was proposed to evaluate the mobility benefits of ASCT. The analysis was based on a 3.3-mile corridor along Mayport Road from Atlantic Boulevard to Wonderwood Drive in Jacksonville, Florida. The proposed analysis was used to estimate the possible dates that separate the two operating characteristics, i.e., with and without ASCT. Also, the posterior estimated distributions were used for the Bayesian hypothesis test to investigate if there is a significant difference in the operating characteristics for two scenarios - with and without ASCT. The results revealed that ASCT increases travel speeds by 4% in typical days of the week (Tuesday, Wednesday and Thursday) in the northbound direction. However, the implementation of ASCT did not yield a significant increase in travel speed in the southbound direction. In addition, ASCT exhibited more benefits in AM peak in the northbound direction indicating a 7% increase in travel speeds. A Bayesian hypothesis test revealed that there is a significant difference in the operating characteristics between scenarios with and without ASCT.

Moreover, an observational before-after Empirical Bayes (EB) with a comparison-group approach was adopted to develop the Crash Modification Factors (CMFs) for certain crash types (total and rear-end crashes) and crash severity levels (fatalities and injury crashes). The CMFs developed were used to quantify the safety benefits of the ASCT. The analysis was based on 42 treatment intersections with ASCT and their corresponding 47 comparison intersections without ASCT. Florida-specific Safety Performance Functions (SPFs) for total and rear-end crashes and for fatal plus injury crashes were also developed. The deployment of ASCT was found to reduce total crashes and rear-end crashes by 5.2% (CMF = 0.948) and 10.6% (CMF = 0.894), respectively. On the other hand, fatal plus injury crashes and PDO crashes were reduced by 6.1% (CMF = 0.939) and 5.4% (CMF = 0.946), respectively, after the ASCT deployment. The CMFs for total crashes and rear-end crashes, and for fatal plus injury crashes and PDO crashes were found to be statistically significant at 95% confidence level. These findings provide researchers and practitioners with an effective means for quantifying the mobility and safety benefits of ASCT, economic appraisal of the ASCT as well as a key consideration to transportation agencies for future ASCT deployment in the state.

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