3 citations · 4 across the 4 of their papers we have counts for
4 papers
Novel pre-emptive control solutions for V2X connected electric vehicles
Kai Man So, Gaetano Tavolo, Davide Tavernini +4
V2X technologies will become widespread in the next generation of passenger cars, and enable the development of novel vehicle control functionalities. Although a wide literature de…
Nonlinear Model Predictive Control for Preview-Based Traction Control
Gaetano Tavolo, Kai Man So, Davide Tavernini +2
This study presents a nonlinear model predictive control (NMPC) formulation for preview-based traction control, which uses the information on the expected tire-road friction coeffi…
Decision Making for Autonomous Driving in Interactive Merge Scenarios via Learning-based Prediction
Salar Arbabi, Davide Tavernini, Saber Fallah +1
Autonomous agents that drive on roads shared with human drivers must reason about the nuanced interactions among traffic participants. This poses a highly challenging decision maki…
Learning an Interpretable Model for Driver Behavior Prediction with Inductive Biases
Salar Arbabi, Davide Tavernini, Saber Fallah +1
To plan safe maneuvers and act with foresight, autonomous vehicles must be capable of accurately predicting the uncertain future. In the context of autonomous driving, deep neural…