TORCS, The Open Racing Car Simulator

By E. Espié, Christophe Guionneau, Bernhard Wymann, Christos Dimitrakakis, Rémi Coulom, Andrew Sumner. 2005

519 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Reinforcement Learning

Citations in the corpus

Asynchronous Methods for Deep Reinforcement Learning (2016, methodology): “We performed further comparisons using the TORCS 3D car racing simulator (Wymann et al., 2013).”
Programmatically Interpretable Reinforcement Learning (2018, methodology): “We use N DPS to generate controllers for cars in The Open Racing Car Simulator (T ORCS ) (Wymann et al., 2014).”
The Hanabi Challenge: A New Frontier for AI Research (2019, background): “thms [26] demonstrates stability, scalability and good performance on a range of singleagent tasks, including the suite of games from the Arcade Learning Environment [21], the TORCS driving simulator [27], and 3D rst-person environments [28]. In the original implementation, the policy is represented”
CARLA: An Open Urban Driving Simulator (2017, methodology): “Open-source racing simulators such as TORCS [28] do not present the com-1st Figure 1: A street in Town 2, shown from a third-person view in four weather conditions.”
IQA: Visual Question Answering in Interactive Environments (2017, background): “Several of these are also interactive making them suitable to learn con-trol, including [5, 30, 35, 39, 72].”
MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments (2017, methodology): “The TORCS (Wymann et al., 2014) and CARLA (Dosovitskiy et al., 2017) simulators have been used to study autonomous driving policies.”
Visual Semantic Planning Using Deep Successor Representations (2017, background): “A common treatment is to use simulation as mental rehearsal before real-world deployment [4, 21, 26, 53, 54].”
Teaching UAVs to Race: End-to-End Regression of Agile Controls in Simulation (2017, methodology): “[4] use TORCS (The Open Racing Car Simulator) [45] to train a DNN to drive at casual speeds through a course and properly pass or follow other vehicles in its lane.”
Teaching UAVs to Race Using UE4Sim (2017, methodology): “[4] uses TORCS (The Open Racing Car Simulator) [43] to train a DNN to drive at casual speeds through a course and properly pass or follow other vehicles in its lane.”
LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving (2020, background): “Some of the earlier simulators [14], [15] run autonomous vehicles in virtual environments, but lack important features such as support for different sensors and simulating pedestrians.”
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors (2021, background): “Researchers have leveraged racing games [41, 33] and developed higher fidelity simulators [19, 4] to train and evaluate self-driving systems.”