Alanna Quail

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About

Alanna Quail is a researcher specializing in autonomous driving systems, Advanced Driver Assistance Systems (ADAS), and rapid prototyping methodologies for intelligent vehicles. Her work sits at the intersection of control systems engineering and automotive technology, focusing on making autonomous vehicle development more accessible and efficient. Among her most notable contributions is her work on the FEV-Driver platform, a cost-effective autonomous development system built on a converted electric go-kart, which demonstrated that robust ADAS research could be conducted without prohibitive hardware costs. This practical approach to platform design reflects a broader commitment to democratizing autonomous vehicle research. Complementing this, her 2019 work on rapid prototyping using ROS and Simulink addressed the growing need for streamlined development pipelines in ADAS and autonomous driving, helping researchers and engineers bridge the gap between simulation and real-world deployment more efficiently. Both papers have garnered 5 citations each, contributing to the emerging body of literature on scalable, accessible autonomous vehicle development frameworks. Quail's research is particularly valuable for early-stage researchers and engineers seeking pragmatic, cost-conscious approaches to building and testing autonomous systems, making her work an important reference point in the evolving landscape of intelligent transportation technology.