LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving
By Guodong Rong, B. Shin, Hadi Tabatabaee, Q. Lu, Steve Lemke, Martins Mozeiko, Eric Boise, Geehoon Uhm, Mark Gerow, Shalin Mehta and 7 more. 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020
536 citations recorded by the source corpus.
Testing autonomous driving algorithms on real autonomous vehicles is extremely costly and many researchers and developers in the field cannot afford a real car and the corresponding sensors. Although several free and open-source autonomous driving stacks, such as Autoware and Apollo are available, choices of open-source simulators to use with them are limited. In this paper, we introduce the LGSVL Simulator which is a high fidelity simulator for autonomous driving. The simulator engine provides end-to-end, full-stack simulation which is ready to be hooked up to Autoware and Apollo. In addition, simulator tools are provided with the core simulation engine which allow users to easily customize sensors, create new types of controllable objects, replace some modules in the core simulator, and create digital twins of particular environments.
Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/65b58efdd4c04bb501244a8f825b28dcba788b60
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Citations in the corpus
- Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing (2022, methodology): “The SVL Simulator is offering both a 3D-vehicle model of the F1TENTH and the Indy Autonomous Challenge vehicle with different racetracks (Figure 11).”