AI-Assisted for Modeling Multitasking Driver

Abstract

Driving a vehicle is one of the most complicated tasks for the artificial intelligence algorithms to learn and perform well. One of the approaches to tackle this problem towards creating fully autonomous cars is to understand the human driver. The human driver behind the wheel, acts as a multitask agent whose main task is driving, but also interacts with other passengers, in-car entertainment and information systems, or her mobile devices. In this thesis, we will create an AI agent using Reinforcement Learning algorithms to model the multitasking driver behavior.