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.

B Ravi Kiran - CatalyzeX

Sensors, Free Full-Text

Human-inspired autonomous driving: A survey - ScienceDirect

LayoutBench Dataset

NY Contract with MCI Worldcom 2003

LiDAR Snowfall Simulation for Robust 3D Object Detection (CVPR 2022) - Algolux

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

Generalization of TORCS car racing controllers with artificial neural networks and linear regression analysis - ScienceDirect

PDF] Study and Comparison of General Purpose Fuzzers

Machine Learning Datasets

PDF) Perspective, Survey and Trends: Public Driving Datasets and Toolsets for Autonomous Driving Virtual Test

第14回 配信講義 計算科学技術特論A（2021）

Autonomous Driving

Adversarial Reinforcement Learning for Steering Cars from Virtual to Real World