论文标题
简短的行业论文：基础设施增强自动驾驶系统中自适应数据融合的必要性
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System
论文作者
论文摘要
本文是第一个提供彻底的系统设计概述以及融合方法选择标准的现实世界合作自动驾驶系统的选择标准，该系统名为基础架构增强自主驾驶或IAAD。我们在路边和车辆侧计算和通信平台上介绍了IAAD硬件和软件的深入介绍。我们在现实部署方案的背景下广泛地表征了IAAD系统，并观察到沿着道路波动的网络状况是目前用于合作自动驾驶的主要技术障碍。为了应对这一挑战，我们提出了新的融合方法，称为“框架间融合”和“计划融合”，以补充当前最新的“框架内融合”。我们证明，每个融合方法都有其自身的好处和约束。
This paper is the first to provide a thorough system design overview along with the fusion methods selection criteria of a real-world cooperative autonomous driving system, named Infrastructure-Augmented Autonomous Driving or IAAD. We present an in-depth introduction of the IAAD hardware and software on both road-side and vehicle-side computing and communication platforms. We extensively characterize the IAAD system in the context of real-world deployment scenarios and observe that the network condition that fluctuates along the road is currently the main technical roadblock for cooperative autonomous driving. To address this challenge, we propose new fusion methods, dubbed "inter-frame fusion" and "planning fusion" to complement the current state-of-the-art "intra-frame fusion". We demonstrate that each fusion method has its own benefit and constraint.
