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Methods/CARLA

CARLA

CARLA: An Open Urban Driving Simulator

Reinforcement LearningIntroduced 2000422 papers
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Description

CARLA is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous urban driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely.

Source: Dosovitskiy et al.

Image source: Dosovitskiy et al.

Papers Using This Method

Scene-Aware Conversational ADAS with Generative AI for Real-Time Driver Assistance2025-07-14Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection2025-07-11LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving2025-07-08YOLO-APD: Enhancing YOLOv8 for Robust Pedestrian Detection on Complex Road Geometries2025-07-07LLM-based Realistic Safety-Critical Driving Video Generation2025-07-02BIDA: A Bi-level Interaction Decision-making Algorithm for Autonomous Vehicles in Dynamic Traffic Scenarios2025-06-19Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging2025-06-17AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning2025-06-16How Real is CARLAs Dynamic Vision Sensor? A Study on the Sim-to-Real Gap in Traffic Object Detection2025-06-16Ego-centric Learning of Communicative World Models for Autonomous Driving2025-06-09Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration2025-06-04DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving2025-06-01Using Diffusion Ensembles to Estimate Uncertainty for End-to-End Autonomous Driving2025-05-31Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)2025-05-22iPad: Iterative Proposal-centric End-to-End Autonomous Driving2025-05-21HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving2025-05-21Object detection in adverse weather conditions for autonomous vehicles using Instruct Pix2Pix2025-05-13Multi-Objective Reinforcement Learning for Adaptive Personalized Autonomous Driving2025-05-08X-Driver: Explainable Autonomous Driving with Vision-Language Models2025-05-08The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes2025-05-08