Alejandro Díaz-Díaz

Papers

Total Citations

H-Index

About

Alejandro Díaz-Díaz is a leading researcher in autonomous vehicle (AV) technology, specializing in the development of safe, reliable, and modular software architectures for self-driving stacks. His work is foundational to the field, particularly in the integration of High-Definition (HD) maps as "pseudo sensors" that provide a trusted baseline for path planning and map monitoring. By exploiting the OpenDRIVE standard, Díaz-Díaz has advanced how AVs can navigate complex, dynamic environments with greater precision and safety. His most-cited paper (38 citations) introduces a novel approach to leveraging HD maps for robust path planning, while his second-most-cited work (25 citations) presents a ROS-based modular architecture that enables the validation of a complete autonomous driving stack. These contributions are critical for bridging the gap between research and real-world deployment, offering a blueprint for building systems that can operate with reliability exceeding human drivers. Díaz-Díaz’s work is essential reading for engineers and researchers aiming to create scalable, safe autonomous driving solutions.