朝着合作性、预测性驾驶辅助的方向发展

Sayanan Sivaraman, M. Trivedi
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引用次数: 27

摘要

在这项工作中,我们描述了针对合作,预测性驾驶辅助的研究。我们描述了预测性驾驶员辅助系统,其目的是对道路环境进行长期预测,支持驾驶员积极的人机交互。随着先进的传感、计算和算法技术的快速发展,智能汽车正在接近一个可以保持全全景感知的时代。因此,当驾驶员提出要求时,仪表化车辆将可以帮助驾驶员在道路环境中导航。随着预测驾驶辅助系统的开发,跨车辆的协作集成将提高性能和整体道路安全。我们将合作系统的范围划分为四个主要领域:车载系统合作、车辆驾驶员合作、跨车辆合作(V2V)以及车辆和基础设施合作(V2I)。每一级合作都将从数量上提高道路安全性能,并提高复杂性和预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards cooperative, predictive driver assistance
In this work, we describe research directed towards cooperative, predictive driver assistance. We describe predictive driver assistance systems, which aim to make longer-term predictions about the on-road environment, supporting positive HMI with the driver. Given the rapid development of advanced sensing, computational, and algorithmic technologies, intelligent vehicles are now approaching an era in which the vehicle can maintains a full panoramic awareness. Thus, the instrumented vehicle will be available to help the driver navigate the on-road environment, when the driver requests it. As predictive driver assistance systems are developed, it will be shown that cooperative integration, across vehicles, will improve the performance and overall on-road safety. We divide the scope of cooperation systems into four main areas: in-vehicle systems cooperation, vehicle-driver cooperation, cooperation across vehicles (V2V), and finally cooperation with vehicles and infrastructure (V2I). Each level of cooperation will quantitatively improve on-road safety performance, and allow for increased sophistication and prediction.
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