论文标题
基于操纵的城市驾驶数据集和合作车辆应用的模型
A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications
论文作者
论文摘要
自动驾驶的短期未来可以被认为是一种混合场景，在同一环境中，自动化和人类驱动的车辆在同一环境中共存。为了满足这种道路配置的需求，文献中已经引入了许多技术解决方案，例如车辆通信和自动化车辆的预测控制。上述两个解决方案均均均取决于人类驾驶员的驱动数据。在这项工作中，我们研究了当前可用的驾驶数据集，并引入了一个基于实际操纵的驾驶数据集，该数据集是在我们的城市驾驶数据收集活动中收集的。我们还提供了将模式嵌入操作特异性样本中的模型。该模型可以用于分类和预测目的。
Short-term future of automated driving can be imagined as a hybrid scenario in which both automated and human-driven vehicles co-exist in the same environment. In order to address the needs of such road configuration, many technology solutions such as vehicular communication and predictive control for automated vehicles have been introduced in the literature. Both aforementioned solutions rely on driving data of the human driver. In this work, we investigate the currently available driving datasets and introduce a real-world maneuver-based driving dataset that is collected during our urban driving data collection campaign. We also provide a model that embeds the patterns in maneuver-specific samples. Such model can be employed for classification and prediction purposes.
