Yu-Sian Jiang

Papers

Total Citations

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About

Yu-Sian Jiang investigates the frontier of human-robot interaction, specifically within autonomous vehicle navigation. Her research centers on designing collaborative systems where humans and AI work in tandem, addressing critical challenges in shared autonomy and dynamic decision-making. A key contribution is her pioneering work on "human-robot copilot systems" for en-route destination changing, a problem that tests the flexibility of self-driving cars. Her 2018 study on this topic (6 citations) laid groundwork for more responsive autonomy. Jiang further advanced the field by introducing "Goal Blending for Responsive Shared Autonomy" (2021, 5 citations), a novel technique that preserves meaningful human control during critical navigation moments, rather than overriding the driver. This work tackles the fundamental tension between safety and user agency in autonomous vehicles. Her research is notable for its focus on real-world, unpredictable scenarios, moving beyond idealized driving conditions. By demonstrating how to blend human intent with machine efficiency, Jiang’s work is shaping the future of trustworthy and adaptable vehicle automation, directly impacting how we design safer, more intuitive driver-assistance systems.