构建端到端自动驾驶测试平台，实现真实数据驱动的自动场景生成与高效仿真验证。
Toward a Full-Stack Co-Simulation Platform for Testing of Automated Driving Systems
- 基于真实数据自动生成测试场景，打通从数据到仿真闭环
- 融合CarMaker、ROS与Apollo，支持高级自动驾驶功能验证
- 适合自动驾驶研发团队进行系统级测试与算法迭代
虚拟测试已成为加速自动驾驶系统部署的有效手段。然而，现有仿真工具链在将快速自动化场景生成与支持高级自动驾驶能力的仿真环境集成方面仍面临挑战。为此，本文提出一个端到端工具链，能够从真实世界数据中自动生成测试场景，并通过基于CarMaker、ROS和Apollo的协同仿真平台实现高效验证。仿真结果表明该工具链具有良好的有效性。演示视频可在提供的链接中观看：https://youtu.be/taJw_-CmSiY。
原文摘要 · Abstract (English)
Virtual testing has emerged as an effective approach to accelerate the deployment of automated driving systems. Nevertheless, existing simulation toolchains encounter difficulties in integrating rapid, automated scenario generation with simulation environments supporting advanced automated driving capabilities. To address this limitation, a full-stack toolchain is presented, enabling automatic scenario generation from real-world datasets and efficient validation through a co-simulation platform based on CarMaker, ROS, and Apollo. The simulation results demonstrate the effectiveness of the proposed toolchain. A demonstration video showcasing the toolchain is available at the provided link: https://youtu.be/taJw_-CmSiY.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。