CARLA simulator

Dear CARLA users The CARLA team and community go to great lengths continuously expanding the diversity of the CARLA content library to reflect the diversity of traffic environments, buildings, vehicles and road users in real-world driving environments. While CARLA's assets provide a good range of pedestrians ranging from children to adults with different clothing styles it's important to consider that some pavement/crossing users may be utilizing various modes of personal transport or mobility assistance devices. This is why we would like to bring your attention to an excellent, recent asset contribution from the CARLA community. Marc Teuber, working at itemis under the supervision of Andreas Graf and Hamza Ben Haj Ammar, has contributed a wheelchair user pedestrian asset which is now available in the DEV branch of the CARLA simulator. To add a wheelchair to a pedestrian model, first, check that the 'can_use_wheelchair' attribute of your chosen walker blueprint is true. If so, set the 'use_wheelchair' attribute to True then you may spawn a wheelchair user into your simulation. Update your CARLA code and content and check it out now!

📢 A simulation and Autoware integration expert, Synkrotron, has joined the Autoware Foundation. 🚀 🌟 Synkrotron has been a valued contributor to the CARLA simulator ecosystem for many years, and they bolstered their partnership by joining the CARLA consortium last year. Synkrotron has built a comprehensive commercial simulation toolchain based on CARLA, and they want to contribute to facilitating the integration of #CARLA and #Autoware. 🚗 Synkrotron has also been deploying Autoware software (Autoware.AI and Autoware Universe) extensively across a diverse range of hardware platforms, including a bespoke small-scale vehicle model and a commercially available electric vehicle. During this extensive work, Synkrotron identified and executed #optimization and #debugging processes within #Autoware stack components. Synkrotron is committed to contributing these enhancements to the Autoware community through well-documented pull requests to the official Autoware repository. 🔧 Last but not least, Snykrotron also developed a proprietary functional module for #calibration purposes, recognizing the challenges associated with vehicle dynamics calibration in deploying autonomous driving systems. Synkrotron intends to share this tool with the Autoware community, providing detailed documentation and support to ensure its successful integration and utilization. 🤝 Synkrotron plans to join the #Simulation working group primarily; however, they will also collaborate with other working groups where the learnings of Synkrotron can be transferred to the Autoware developer community. 🎉 We welcome Synkrotron to the Autoware Foundation, and we are excited to work with such an experienced partner in developing and deploying solutions for autonomous technology. Visit Synkrotron's website 👉 https://www.synkrotron.ai/ Yuxi Pan Read more in the Autoware Foundation blog 👉 https://lnkd.in/egEJx92N #news #newmember #autoware #opensource #autonomousvehicles #technology #welcome #worktogether

We are delighted to announce the winners of the CARLA CVPR Autonomous Grand Challenge 2024!! The Honorable Runner-up prize is awarded to the Tuebingen AI team, who placed first in the MAP track of the CARLA Leaderboard 2.0 and achieved second place in the SENSORS track. The Outstanding Champion award goes to LLM4AD, who achieved an impressive score of 6.9 in the SENSORS track of the Leaderboard 2.0, 23% ahead of the nearest competitor while also placing second in the MAP track. Additionally, LLM4AD are awarded the Innovation Award, for their innovation in using LLaVa and LLaMA in concert to generate waypoints and select challenging scenarios to focus training efficiently. Congratulations to the winners and to all the competitors who submitted excellent work. For more details about the CVPR Autonomous Grand Challenge go to the website: https://lnkd.in/dvDraz6c Thank you all for participating! We hope to see many of you at the workshop.

Dear CARLA community We are excited to notify you that the Unreal Engine 5 version of CARLA is currently accessible in a designated branch of the CARLA GitHub repository. We encourage you to download and build the repository to start experimenting with the new functionality brought to CARLA by Unreal Engine 5.3 which includes: - Improved scene illumination with Lumen - stunningly realistic reflections and ambient lighting - Improved geometry resolution and performance with Nanite - say goodbye to LODs and welcome geometry which adjusts smoothly and continiously with distance from camera, enabling the use of much more detailed geometry without performance costs This version of CARLA currently includes 1 map, Town 10, and 5 vehicles, all of which have been updated with new materials and textures exploiting UE5's advanced features. Further content from CARLA's content library will be migrated/upgraded in the near future. Check out the UE5 development branch here: https://lnkd.in/dBr7mQqp Note!! - The UE5 version of CARLA is a work in progress. Significant changes will be made to the branch throughout the following year. Some functionality is missing from previous versions of CARLA, while other functionality may be unstable or overhauled. We encourage you to experiment but we strongly discourage any mission-critical work based on this version until an official release. Enjoy!

Check out this amazing documentary detailing the CVC's development of AI for autonomous vehicles operating on rural roads. The project aims towards finding economical and sustainable solutions to public transport in isolated rural areas. CARLA is used to train and test the autonomous agent in simulation within a digital twin of a stunning route through the Catalan Pyrenees. The software is then deployed in real world tests in the Alt Pirineu nature park. https://lnkd.in/d9sxF7Xp

A realistic city generator. Hothifa Smair shared these videos on X which lets to adjust setbacks, height, layout, etc in real time. How does it work? “Powered by Geometry Nodes, this marvelous setup allows the user to easily generate entire cities in Blender, complete with a variety of buildings, roads, lamp posts, traffic lights, parking lots, vegetation, and more, which you can tweak and customize in real-time to get the exact layout you've envisioned. As stated by Hothifa, the generator is nearing its completion and will be available to download sometime very soon.” Thanks to Dimitar Pouchnikov for sharing his thoughts and getting me to check it out. Video shared for educational use. Sources Video source: https://lnkd.in/giZkT8qc https://lnkd.in/gVeCzECJ Dimitar’s post: https://lnkd.in/gFgpe6-G Article: https://lnkd.in/g6tcdjeB Review: https://lnkd.in/gNfn4Q-y

Sim-to-Rerun: Using Rerun to visualize CARLA simulator output through ROS 2. This example visualizes simulated sensor data from the CARLA simulator for autonomous driving in Rerun. It’s built using Rerun’s new proof-of-concept C++ ROS2 bridge, which currently has support for a limited set of message types. Rerun is to our knowledge the most performant multimodal visualizer out there and is already used by some of the best teams in the world. We’re continuing our push to make Rerun useful for more Robotics teams and this example and PoC ROS 2 bridge is another step in that direction. Official ROS 2 and MCAP support will be coming down the line, but in the meantime we hope this example will provide a useful starting point for anyone that wants to use Rerun with their ROS 2 project. You can find a link to the example and ROS 2 bridge in the comments. #ROS #Multimodal #Robotics #Simulation

CloningDCB research is supported by project TED2021-132802B-I00 funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR.

We are excited to share another amazing application of the CARLA simulator from the Instituto de Biomecánica (IBV) in Valencia, Spain, where a team has built a realistic human driving platform driven by the CARLA simulator. The CARLA simulator drives 3 large displays atop a mechanical platform to simulate vehicle movement and a host of sensors to monitor human physiological reactions to driving scenarios. Measurements include eyetracking for creating attention maps along with sensors to measure brain activity and other vital signals of the human driver. The Human Autonomous Vehicle (HAV) helps augment the understanding of the interaction between driver and vehicle, leading to insights for advancement in safety and driver assistance technology. Check out the Instituto de Biomecánica de Valencia's website: https://lnkd.in/dsQFJvqn #adas #simulation #carlasimulator

ARA has entered into an agreement with Embodied AI Foundation to update the CARLA simulator, an open-source simulator for autonomous driving research, to Unreal Engine 5, a powerful and widely used game development engine created by Epic Games. https://lnkd.in/gDXnpC3u