Energy Efficient Controls for Connected Automated Vehicles (CAVs)
Francesco Borrelli, Professor
Mechanical Engineering
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
In this project, we aim to improve the energy performance of connected automated vehicles in real-world scenarios. The energy savings can be obtained by harnessing technologies such as (i) remote computations, (ii) forecasts, (iii) historical data, (iv) automation, and (v) coordination with other vehicles and infrastructure. We have the actual vehicles that we can control longitudinal and latitudinal motions and also technologies that we can utilize vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications.
Role: Building a Carla virtual environment: We are currently building a virtual environment that we can perform preliminary experiments before the actual real-world experiments. The task will include setting up Carla simulations and mapping virtual environments for both (1) Energy Efficient Controls for Connected Automated Vehicles and (2) Autonomous Rover for the Solar Field projects. Learning outcomes from this task can be (i) experiences of Carla which is a famous virtual environment software for autonomous vehicle testings and (ii) vehicle dynamics modeling with control strategies (PID and MPC).
Qualifications: Python is mandatory and ROS background preferably
Day-to-day supervisor for this project: Eric Choi, Graduate Student
Hours: 9-11 hrs
Related website: https://sites.google.com/berkeley.edu/mpcconnectedcars/home
Mathematical and Physical Sciences Engineering, Design & Technologies