论文标题

合作感的演示:连接和自动化车辆操作的安全性和鲁棒性

Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations

论文作者

Shan, Mao, Narula, Karan, Wong, Yung Fei, Worrall, Stewart, Khan, Malik, Alexander, Paul, Nebot, Eduardo

论文摘要

合作感或集体感知(CP)是智能运输系统(ITS)的新兴技术。它使其站(ITS-S)能够通过车辆对X(V2X)通信与他人共享其本地感知信息,从而提高了道路运输的效率和安全性。在本文中,我们介绍了在开发连接和自动化的车辆(CAV)和智能路边单位(IRSU)方面的最新进展。我们提出了三个不同的实验,以证明在智能基础架构中使用CP服务以提高对弱势道路使用者(VRU)的认识,从而在各种交通情况下对CAVS的安全性。我们在实验中证明,连接的车辆(CV)可以“看到”拐角周围的行人。更重要的是,我们证明了骑士如何可以自主,安全地与步行和行人行人互动,仅依靠IRSU通过车辆到基础设施(V2I)通信的CP信息。这是仅使用CP信息的城市车辆自动化的首次演示之一。我们还在论文中介绍了从IRSU收到的集体感知消息(CPM)的处理,并通过不确定性,多个道路用户跟踪以及最终在CAV内的路径计划/决策来通过CP信息坐标转换管道。实验结果是通过手动驱动的CV,完全自主的CAV以及带有视觉和激光传感器的IRSU以及道路用户跟踪系统进行的。

Cooperative perception, or collective perception (CP) is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improved efficiency and safety in road transportation. In this paper, we present our recent progress on the development of a connected and automated vehicle (CAV) and intelligent roadside unit (IRSU). We present three different experiments to demonstrate the use of CP service within intelligent infrastructure to improve awareness of vulnerable road users (VRU) and thus safety for CAVs in various traffic scenarios. We demonstrate in the experiments that a connected vehicle (CV) can "see" a pedestrian around the corners. More importantly, we demonstrate how CAVs can autonomously and safely interact with walking and running pedestrians, relying only on the CP information from the IRSU through vehicle-to-infrastructure (V2I) communication. This is one of the first demonstrations of urban vehicle automation using only CP information. We also address in the paper the handling of collective perception messages (CPMs) received from the IRSU, and passing them through a pipeline of CP information coordinate transformation with uncertainty, multiple road user tracking, and eventually path planning/decision making within the CAV. The experimental results were obtained with manually driven CV, fully autonomous CAV, and an IRSU retrofitted with vision and laser sensors and a road user tracking system.

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