Fernando Garrido

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About

Fernando Garrido is a researcher focused on the intersection of artificial intelligence and autonomous vehicle technology, with a particular emphasis on decision-making and path planning for automated driving. His work addresses critical challenges in how self-driving cars navigate complex environments, from strategic route generation to real-time tactical maneuvers. Garrido’s most cited paper, "Review of Decision-Making and Planning Approaches in Automated Driving" (2022), has garnered 26 citations, reflecting its value as a comprehensive synthesis of the field’s rapid evolution. In this review, he systematically categorizes decision-making processes across strategic, tactical, and operational levels, providing a foundational resource for researchers. His earlier work, "Real-time planning for adjacent consecutive intersections" (2016), introduces a novel local path planning algorithm that enhances trajectory generation and tracking for automated vehicles navigating dense urban settings. Though less cited, this paper demonstrates his hands-on contributions to practical, real-time solutions. Garrido’s research bridges theoretical frameworks and applied robotics, making him a notable voice in advancing safe and efficient autonomous driving systems.