no code implementations • 16 Oct 2023 • Jacob Paugh, Zhaoxuan Zhu, Shobhit Gupta, Marcello Canova, Stephanie Stockar
Connected and autonomous vehicles have the potential to minimize energy consumption by optimizing the vehicle velocity and powertrain dynamics with Vehicle-to-Everything info en route.
no code implementations • 25 May 2021 • Zhaoxuan Zhu, Nicola Pivaro, Shobhit Gupta, Abhishek Gupta, Marcello Canova
Connected and Automated Hybrid Electric Vehicles have the potential to reduce fuel consumption and travel time in real-world driving conditions.
Model-based Reinforcement Learning reinforcement-learning +1
no code implementations • 3 Apr 2021 • Zhaoxuan Zhu, Shobhit Gupta, Nicola Pivaro, Shreshta Rajakumar Deshpande, Marcello Canova
Predictive energy management of Connected and Automated Vehicles (CAVs), in particular those with multiple power sources, has the potential to significantly improve energy savings in real-world driving conditions.
no code implementations • 13 Jan 2021 • Zhaoxuan Zhu, Shobhit Gupta, Abhishek Gupta, Marcello Canova
Connected and Automated Vehicles (CAVs), in particular those with multiple power sources, have the potential to significantly reduce fuel consumption and travel time in real-world driving conditions.