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My Projects

Focusing on emerging and sustainable urban mobility, my past and present projects include establishing statewide bicycle & pedestrian count programs and evaluating the impacts of shared electric scooters. 



1. Bicycle and pedestrian count

This project evaluated nonmotorized vehicle count methods and technologies and developed recommendations to integrate them into Tennessee's statewide count program. We first did a nationwide scan of best practices for bicycle and pedestrian counts from leading transportation agencies. Then, we developed a semi-structured questionnaire to interview representatives of Tennessee's transportation agencies to assess existing count efforts. The resulting report comprehensively describes the capabilities of count technologies and strategies, followed by methods to implement and interpret count data. We also recommend five goals that can guide the Tennessee Department of Transportation (TDOT)’s efforts to support improvements in nonmotorized counts across the state.

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2. Sustainability 

Supported by the Oak Ridge National Laboratory’s (ORNL) Graduate Advancement, Training, and Education (GATE) program, this study proposes a framework to implement standardized micromobility data to evaluate the energy and emission impacts of shared e-scooters related to system operations and modal shift. The findings of the proposed analysis are expected to help city governments understand the overall environmental impact of shared e-scooters and develop data-driven strategies to manage their transportation-related sustainability impacts. 

3. Safety 

In the first of its kind, I conducted a comprehensive research-to-practice study to understand the demographics, circumstances and mechanisms involved in motor vehicle-e-scooter and motor vehicle-bicycle crashes, using Version 3 of the Pedestrian and Bicycle Crash Analysis Tool (PBCAT). I found that the characteristics of e-scooter and bicycle crashes do not fully overlap. The findings could help avoid e-scooter and motor vehicle crashes, which contribute to 80% of e-scooter rider fatalities.  

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4. Demand elasticity

This research project scrutinizes shared e-scooter demand (trip information) and supply (vehicles deployed) to estimate the demand elasticity of deployed e-scooter vehicles and cost per minute. I found that that the number of trips didn’t increase proportionally to the number of e-scooters deployed. These findings could be helpful for city governments to identify the optimal number of service providers and fleet sizes to permit so that demand is fulfilled without an oversupply of e-scooter vehicles in public spaces. 

5. Usage pattern of e-scooters 

This study proposes a framework for high-resolution analysis of micromobility data to identify distinct e-scooter usage patterns using Principal Component Analysis (PCA) and a K-means unsupervised machine learning algorithm. Scrutinizing over a million e-scooter trips in Nashville, Tennessee, I found five distinct e-scooter usage patterns, and assigned possible trip purposes based on the time of day and starting/ending locations of the trips. The findings of this study can help city administrations, planners, and micromobility operators make data-driven decisions based on the understanding of when and where people are using e-scooters.

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Image by Laurentiu Morariu

6. Micromobility adoption

While most sustainable transportation-related studies within the developing world focus on megacities, there are limited studies in mid-sized cities (more than 500,000 and less than 5 million in population), which make up an “overwhelming majority” of the world’s cities and have the highest population growth rate. This study evaluates individuals’ perception of and propensity to adopt shared micromobility as an emerging urban mobility solution. The findings of the project can benefit policymakers, urban planners, transportation engineers, and entrepreneurs in introducing or improving shared micromobility systems in mid-sized cities of developing countries. 

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