Alessandro Bettoni
Papers
1
Total Citations
5
H-Index
1
About
Alessandro Bettoni is a researcher at the forefront of autonomous racing, specializing in data-driven motion planning and predictive control for high-speed competitive environments. His work addresses the critical challenge of head-to-head racing, where anticipating opponent behavior is essential for safe and effective overtaking. Bettoni’s most notable contribution is the "Predictive Spliner," a novel overtaking planner that leverages Gaussian Process regression to model and predict opponent trajectories, enabling an autonomous vehicle to execute strategic passes with improved reliability. This data-driven approach has garnered attention in the autonomous racing community, with his 2024 paper already accumulating 5 citations—a strong signal of its early impact. Beyond this, Bettoni’s research intersects with model predictive control and learning-based methods for dynamic, uncertain environments. His work not only advances the state of the art in autonomous motorsport but also offers transferable insights for broader applications in robotics and intelligent transportation systems, where real-time decision-making under uncertainty is paramount.
Research Focus
Key Achievements
Top Papers
- 1