Autonomous Vehicles

In the last couple of years, Autonomous Vehicles (AVs) and self-driving cars began to migrate from laboratory development and testing conditions to driving on public roads. Their deployment in our environmental landscape offers a decrease in road accidents and traffic congestions, as well as an improvement of our mobility in overcrowded cities. The main drivers behind this automotive revolution are the advances in artificial intelligence and deep learning.

An autonomous vehicle is an intelligent agent which observes its environment, makes decisions and performs actions based on these decisions. The driving functions map sensory input to control output and are implemented either as modular perception-planning-action pipelines, End2End or Deep Reinforcement Learning systems which directly map observations to driving commands (turn left, turn right, accelerate, decelerate). In a modular pipeline, the main problem is divided into smaller sub-problems, where each module is designed to solve a specific task and deliver the outcome as input to the adjoining component.

Related projects

Related publications

L. Marina, B. Trasnea, C. Tiberiu, A. Vasilcoi, F. Moldoveanu and S.M. Grigorescu, “Deep Grid Net (DGN): A Deep Learning System for Real-Time Driving Context Understanding”, Int. Conf. on Robotic Computing IRC 2019, Naples, Italy, February 25-27, 2019.

B. Trasnea, L. Marina, A. Vasilcoi, C. Pozna and S.M. Grigorescu, “GridSim: A Vehicle Kinematics Engine for Deep Neuroevolutionary Control in Autonomous Driving”, Int. Conf. on Robotic Computing IRC 2019, Naples, Italy, February 25-27, 2019.

S.M. Grigorescu "Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision", Int. Conf. on Robotics and Automation ICRA 2018, Brisbane, Australia, May 21-25, 2018.

S.M. Grigorescu M. Glaab and J. Schlosser "KI für Selbstfahrende Autos (Artificial Intelligence for Self-Driving Cars)", EE Faszination Elektronic, 2017.

S.M. Grigorescu M. Glaab and A. Roßbach "From logistic regression to self-driving cars: Chances and challenges of using machine learning for highly automated driving", Elektrobit Automotive TechPaper, 2017.

B. Trasnea, G. Macesanu, S.M. Grigorescu and T. Cocias, "Smartphone Based Mass Traffic Sign Recognition for Real-time Navigation Maps Enhancement" Int. Conf. on Optimization of Electrical and Electronic Equipment, Brasov, Romania, 25-27 May 2017.

L. Marina, F. Moldoveanu and S.M. Grigorescu "Environment perception in racing simulators using deep neural networks", Int. Conf. on Optimization of Electrical and Electronic Equipment, Brasov, Romania, May 25-27, 2017.