ConScenD

ConScenD数据集是由fka GmbH和RWTH Aachen University汽车工程研究所合作创建的，旨在根据UNECE R157法规为自动驾驶系统提供具体场景测试。该数据集包含超过340个从德国高速公路自然驾驶数据集highD中提取的具体场景，用于模拟和验证自动驾驶系统的安全性。创建过程中，研究团队采用了一种从真实世界数据中提取场景参数的方法，并将这些参数转换为模拟环境中的可执行测试案例。ConScenD数据集主要应用于自动驾驶系统的安全评估，特别是在解决复杂交通场景下的系统级模拟需求。

The ConScenD dataset was co-developed by fka GmbH and the Institute of Automotive Engineering at RWTH Aachen University, aiming to provide scenario-specific test cases for automated driving systems in compliance with UNECE Regulation R157. This dataset includes over 340 specific scenarios extracted from the German highway naturalistic driving dataset highD, which is used for simulating and validating the safety of automated driving systems. During its development, the research team adopted a methodology for extracting scenario parameters from real-world driving data, and converted these parameters into executable test cases within simulation environments. The ConScenD dataset is primarily applied to the safety assessment of automated driving systems, particularly to address the system-level simulation requirements in complex traffic scenarios.