- CARLA Simulator
CARLA has been developed from the ground up to support development, training, and validation of autonomous 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
- CARLA 0. 9. 16 Release - CARLA Simulator
We are thrilled to present to you the CARLA 0 9 16 release! This version brings some major upgrades to the Unreal Engine 4 26 version of CARLA that promise to augment your CARLA workflow and enhance the diversity of your simulation data!
- CARLA 0. 10. 0 Release with Unreal Engine 5. 5! - CARLA Simulator
The CARLA team is excited to announce the release of CARLA version 0 10 0 The biggest news is that this version delivers a monumental leap forward in visual fidelity through a migration from Unreal Engine 4 26 to Unreal Engine 5 5
- Get Ready for CARLA 0. 9. 16 this summer! - CARLA Simulator
With just a few clicks, users can generate a CARLA environment grounded in the real world — ideal for geo-specific experiments, regulatory testing, and sim-to-real pipelines
- CARLA 0. 9. 15 Release - CARLA Simulator
This version brings SimReady content import to CARLA through NVIDIA’s Omniverse platform, 2 new maps, a procedural map generation tool and a procedural building generation tool to accelerate and enhance your CARLA content creation process
- Blog - CARLA Simulator
In this new release, we provide two new and exciting cities, new pedestrian models and animations and introducing the new no-rendering mode visualization for CARLA
- CARLA Ecosystem
The CARLA-Apollo bridge connects the two popular open-source software packages, enabling Apollo software stacks to drive the CARLA simulator and receive, assimilate, interpret and visualize data through the extensively featured Apollo interface Check out the GitHub repository
- NVIDIA Omniverse Cloud APIs - CARLA Simulator
With NVIDIA Omniverse Cloud APIs, CARLA has become more than just a simulator; it’s also a powerhouse for accelerating AV development It’s about making the development process more efficient, reducing the reliance on physical prototypes, and, ultimately, crafting the future of autonomous driving
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