观察道路上的车辆行为:问题、方法和观点

Sayanan Sivaraman, B. Morris, M. Trivedi
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引用次数: 12

摘要

在这项工作中,我们回顾了最近的工作,包括智能交通的一个新兴领域:车辆行为分析。ITS社区已经从基于车辆和基于基础设施的传感两方面着手解决这个问题。在这两种情况下,动作都是行为表征所需的关键指标,准确的长期预测是最终目标。然而,流行的行为表征方法在传感方法之间存在差异。车载传感往往侧重于与各种特征相结合的时空测量,以准确估计目标状态。相比之下,基础设施感知倾向于避免尝试对车辆状态进行高分辨率估计,而倾向于利用聚合学习的模式进行约束估计。这篇综述的重点是基于视觉的传感,并提供了用于监视和道路视觉模式的最新方法的重点。我们对该领域的未来发展方向进行了讨论和评论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Observing on-road vehicle behavior: Issues, approaches, and perspectives
In this work, we review recent works comprising an emerging field of intelligent transportation: behavior analysis of vehicles. The ITS community has approached this topic both from vehicle-based and infrastructure-based sensing. In both cases, motion is the key indicator required for behavioral characterization, with accurate long-term prediction being the ultimate goal. However, the popular methods for behavior characterization differ between the sensing methodologies. Vehicle-based sensing tends to focus on spatio-temporal measurements coupled with various features for accurate estimation of object state. In contrast, infrastructure-sensing tends to avoid attempting high resolution estimation of vehicle state and prefers to utilize patterns learned in aggregate for constrained estimation. This review focuses on vision-based sensing and provides highlights of state-of-the art methods used in surveillance, and on-road vision modalities. We provide discussion and comment on future directions in the field.
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