New publication: Deep Reinforcement Learning and Imitation Learning for Autonomous Parking Simulation

In recent years, system intelligence has revolutionized various domains, including the automotive industry, which has fully incorporated intelligence through the emergence of Advanced Driver Assistance Systems (ADAS). Within this transformative context, Autonomous Parking Systems (APS) have emerged as a foundational component, revolutionizing the way vehicles navigate and park with precision Read more…

New publication:On-Road Autonomous Vehicle Navigation In A Dynamic Environment Using Deep Reinforcement Learning, Towards Fuel Consumption Optimization

In this work we explore the application of deep reinforcement learning (DRL) in navigating autonomous vehicles (AVs) within dynamic environments, aiming to optimize fuel efficiency without compromising safety or operational reliability. Focusing on the intricate balance between real-time decision-making and energy conservation, a DRL model was developed that efficiently manages Read more…