Paulo Resende

Valeo (France), Institut national de recherche en sciences et technologies du numérique

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About

Paulo Resende is a leading researcher in autonomous vehicle systems, with a focus on decision-making, localization, and cooperative automation. His work spans strategic, tactical, and operational levels of automated driving, addressing how vehicles plan routes, navigate environments, and coordinate with one another. Resende’s most-cited paper, “Review of Decision-Making and Planning Approaches in Automated Driving” (2022, 26 citations), provides a comprehensive taxonomy of decision-making frameworks, serving as a key reference for researchers and engineers advancing autonomous navigation. He also developed the “Geodetic Normal Distribution Map” for long-term LiDAR localization (2020, 7 citations), a novel approach that overcomes the scalability limitations of traditional point cloud maps for mass-produced vehicles. Earlier, Resende contributed to the CityMobil project (2012, 3 citations), demonstrating a cooperative personal automated transport system with multiple driverless vehicles navigating outdoor environments. His more recent work on loosely-coupled localization fusion (2023, 2 citations) addresses bias alignment for robust multi-sensor integration. With a career bridging foundational research and real-world deployment, Resende’s contributions are shaping the future of safe, scalable, and cooperative automated driving systems.