TORCS Dataset Papers With Code

TORCS (The Open Racing Car Simulator) is a driving simulator. It is capable of simulating the essential elements of vehicular dynamics such as mass, rotational inertia, collision, mechanics of suspensions, links and differentials, friction and aerodynamics. Physics simulation is simplified and is carried out through Euler integration of differential equations at a temporal discretization level of 0.002 seconds. The rendering pipeline is lightweight and based on OpenGL that can be turned off for faster training. TORCS offers a large variety of tracks and cars as free assets. It also provides a number of programmed robot cars with different levels of performance that can be used to benchmark the performance of human players and software driving agents. TORCS was built with the goal of developing Artificial Intelligence for vehicular control and has been used extensively by the machine learning community ever since its inception.

PDF) The WCCI 2008 simulated car racing competition

Sohan Rudra - Research Associate - Technische Universität Darmstadt

PDF] Distributed Approach for implementation of A3C on TORCS

Autonomous Driving

Waymo Open Dataset Dataset

Neural Networks in Python: From Sklearn to PyTorch and Probabilistic Neural Networks

NY Contract with MCI Worldcom 2003

Newsletters Papers With Code

Overview of the online TORCS controller evolution in the online UL-ERL

BDCC, Free Full-Text

Adversarial Reinforcement Learning for Steering Cars from Virtual to Real World