Takatsugu Hirayama
Papers
4
Total Citations
43
H-Index
3
About
Takatsugu Hirayama is a researcher whose work sits at the intersection of autonomous systems, human-robot interaction, and intelligent transportation. His research spans robot localization, pedestrian behavior analysis, and driver gaze modeling — fields central to the safe deployment of automated vehicles and mobility systems. Hirayama's most recognized contribution is his 2020 proposal of a hybrid localization framework that intelligently fuses Monte Carlo localization with CNN-based end-to-end approaches via importance sampling, earning 25 citations and demonstrating a practical path toward more robust autonomous navigation. His work extends beyond technical systems into understanding human factors: he has investigated how pedestrians visually respond to automated vehicles whose intentions are unclear, and how driver experience shapes eye-gaze strategies when operating robotic wheelchairs in complex environments. These studies collectively contribute to safer human-machine interaction design. His 2019 work on safety criteria for personal mobility vehicles at blind corners further illustrates his commitment to translating research into actionable engineering guidelines. Across his portfolio, Hirayama consistently bridges machine intelligence and human behavior, making his work valuable to researchers in robotics, autonomous driving, and accessibility technology alike.
Research Focus
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Top Papers
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