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Ubiquitous Sensing for Enhanced Road Situational Awareness: A Target-Tracking Approach

机译:无所不在的传感技术可增强道路状况意识:一种目标跟踪方法

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Situational awareness on road networks, defined with respect to perception of adverse road conditions (e.g., potholes) in addition to motorists, pedestrians and other artifacts that are crucial to enabling autonomous driving functionality, is a critical requirement for a multitude of applications in intelligent transportation systems where an increasing number of autonomous vehicles are expected to be present. For instance, ride comfort, which is adversely affected by road anomalies, is a much more pronounced concern for autonomous vehicles where humans are driven (most likely as a paid service) compared to traditional automobiles (being driven by humans). Towards developing efficient and cost-effective solutions for generating timely road situational awareness data, this paper describes a target-tracking formulation that exploits ubiquitous sensing and processing capabilities in modern automobiles. The problem formulation presented in this paper is fundamentally different to the traditional target tracking as voluntarily participating motor-vehicles are used as mobile sensors for detection and tracking in comparison to sensors that actively detect and track targets. A simplified example on initial detection and tracking the evolution of potholes is utilized for illustration of the proposed concept.
机译:除了驾驶员,行人和其他对实现自动驾驶功能至关重要的人工制品外,还根据对不利道路条件(例如坑洼)的感知来定义的道路网络态势感知,是智能交通中众多应用的关键要求预计将会出现越来越多的自动驾驶汽车的系统。例如,与传统汽车(由人类驾驶)相比,受到道路异常影响的乘坐舒适性是自动驾驶汽车(最有可能作为有偿服务)驾驶的地方,这种驾驶舒适性受到人们的关注。为了开发有效和具有成本效益的解决方案以生成及时的道路状况意识数据,本文描述了一种目标跟踪公式,该公式利用了现代汽车中普遍存在的感应和处理能力。本文提出的问题表述与传统的目标跟踪根本不同,因为与主动检测和跟踪目标的传感器相比,自愿参与的机动车辆被用作检测和跟踪的移动传感器。利用有关初始检测和跟踪坑洞演变的简化示例来说明所提出的概念。

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