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] Distributed Approach for implementation of A3C on TORCS

Autonomous Driving

Service-Oriented Computing and System Integration: Software, IoT, Big Data, and AI as Services

Sensors, Free Full-Text

Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis

第14回 配信講義 計算科学技術特論A（2021）

Matthew Muckley on LinkedIn: Announcing version 2.0 of the fastMRI dataset · Discussion #284 ·…

BDCC, Free Full-Text

Adversarial Reinforcement Learning for Steering Cars from Virtual to Real World

Graphical TORCS driver model and the corresponding training configurations.

Sohan Rudra - Research Associate - Technische Universität Darmstadt

B Ravi Kiran - CatalyzeX

Pseudo-code of dynamic scheduling framework with grouped whales (DSF.GW)

Deep reinforcement learning for autonomous vehicles: lane keep and overtaking scenarios with collision avoidance