TORCS Dataset Papers With Code
Por um escritor misterioso
Descrição
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.
Information, Free Full-Text
B Ravi Kiran - CatalyzeX
Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env - Artificial Intelligence Research
Traffic Simulation and Autonomous Driving Experiment in VIPLE
Learning a Driving Simulator – arXiv Vanity
Pseudo-code of dynamic scheduling framework with grouped whales (DSF.GW)
BURST Dataset Papers With Code
attention_and_driving/self-driving.md at 2.0 · ykotseruba/attention_and_driving · GitHub
Yet Another Driving Simulator OpenROUTS3D: The Driving Simulator for Teleoperated Driving
Machine Learning Datasets
Sensors, Free Full-Text
PDF] Distributed Approach for implementation of A3C on TORCS
UvA autonomous driving: Labbook 2020
Deep reinforcement learning for autonomous vehicles: lane keep and overtaking scenarios with collision avoidance
