| KEYWORD |
AI-powered driving style estimation and driver mimicking
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, AUTONOMOUS CONNECTED CARS, MACHINE LEARNING
Reference persons FABRIZIO LAMBERTI
Research Groups DAUIN - GR-09 - GRAphics and INtelligent Systems - GRAINS
Thesis type THESIS WITH A COMPANY
Description The driving style is unique to each person and it affects the vehicle usage. The thesis aims to create an autonomous agent able to mimic the behavior of a specific driver, in order to perform adaptive DSE (Drive Style Estimation). This requires the agent to be able both to react properly to environmental stimuli and to tailor its behavior on the driver’s profile. Activities could encompass the use of the both datasets collected on real vehicles, as well as data gathered in simulated environments.
The thesis will be carried out in collaboration with Sensor Reply.
The student will be involved in:
- Vehicle data analysis and data preprocessing;
- Development of an AI-powered autonomous agent;
- Adapt the agent to the specific driver.
Relevant technologies: Deep Learning, Adversarial Learning, Reinforcement Learning, Autonomous Agent, Edge AI, Cloud Computing, Connected Vehicle
See also http://grains.polito.it/work.php
Deadline 31/07/2023
PROPONI LA TUA CANDIDATURA