Date of Award
College of Science, Engineering, and Technology (COSET)
MS in Transportation Planning & Management
Committee Member 1
Committee Member 2
Committee Member 3
Committee Member 4
Environmental Justice, In-Service Performance Evaluation, Machine Learning, Roadside Safety Devices, Transportation Equity
Transportation equity plays an important role in modern communities, and a fair distribution of transportation infrastructures is vital as an integral part of transportation planning process. The In-Service Performance Evaluation (ISPE) satisfies transportation safety requirements by identifying the problems of roadside safety devices during installation and maintenance process with proper solutions, and the performance results reveal the current statue of target devices in specific areas. Although several studies have been conducted to emphasize transportation equity, there is still a lack of equity research specifically focusing on the deploying of roadside safety devices associated with ISPE results. With proper comparison of in-service performance results in different areas, the importance of ensuring transportation equity of all communities and areas in the decision-making process is able to be demonstrated. This thesis utilizes Machine Learning models to analyze linked crash and roadway data related to major roadside safety devices implemented in Texas. Three typical roadside safety devices are selected to be assessed, including: (1) guardrail, (2) median barrier, and (3) bridge rail. By comparing both statistical and Machine Learning based modeling analysis with rural and metropolitan areas in specific counties, it is demonstrated that distributions of crashes that end up causing heavy property damage or serious injuries is higher in rural communities regardless of its lower crash frequency. The data analysis result suggests that parameters related to roadway conditions and transportation infrastructures tend to have higher influence over the performances of rural safety devices. Additional one year of crash data analysis also addresses the importance of transportation equity under the COVID-19 pandemic period. Recommendations on improving overall equity and Environmental Justice (EJ) within all regions are conducted with stated findings.
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Wang, Hanzhen, "Addressing Transportation Equity by Comparing In-Service Performance of Roadside Safety Devices through Machine Learning Modeling" (2021). Theses (2016-Present). 20.