Set-Based Prediction of Pedestrians in Urban Environments Considering Formalized Traffic Rules
Set-Based Prediction of Pedestrians in Urban Environments Considering Formalized Traffic Rules
复制标题
考虑正式交通规则的城市环境中行人的基于集合的预测
DOI：
10.1109/itsc.2018.8569434
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
M. Althoff
中科院分区：
文献类型：
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作者：
Markus Koschi;Christian Pek;Mona Beikirch;M. Althoff
基于集合的预测可以确保计划运动的安全性，因为它们提供了一个有界区域，其中包括其他交通参与者的不确定性模型的所有可能的未来状态。然而，尽管自动驾驶汽车在城市环境中进行了测试，但针对行人的基于集合的预测还不存在。本文针对这个问题，并提出了一种基于集的预测行人可达性分析的方法。我们通过结合行人的动态、上下文信息和交通规则来获得行人可达占用率的紧密过近似。此外，由于行人经常无视交通规则，我们的约束自动适应，使这些行为包括在预测中。使用记录的行人数据集，我们验证了我们提出的方法，并证明其用于自动驾驶汽车的规避机动规划。
Set-based predictions can ensure the safety of planned motions, since they provide a bounded region which includes all possible future states of nondeterministic models of other traffic participants. However, while autonomous vehicles are tested in urban environments, a set-based prediction tailored to pedestrians does not exist yet. This paper addresses this problem and presents an approach for set-based predictions of pedestrians using reachability analysis. We obtain tight over-approximations of pedestrians' reachable occupancy by incorporating the dynamics of pedestrians, contextual information, and traffic rules. In addition, since pedestrians often disregard traffic rules, our constraints automatically adapt so that such behaviors are included in the prediction. Using datasets of recorded pedestrians, we validate our proposed method and demonstrate its use for evasive maneuver planning of automated vehicles.