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Towards trusted autonomous vehicles from vulnerable road users perspective

机译：从弱势道路使用者的角度转向可信赖的自动驾驶汽车

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A number of recent research projects in human-vehicle interaction field are addressing the problem of human trust in autonomous vehicles. Almost all of these work are focusing on investigating the attributes and the factors that influence the human drivers' trust of these vehicles. However, a little research has been done on the bystander humans' trust of autonomous vehicles. Bystander humans in the context of autonomous vehicles, are humans that does not explicitly interact with the automated vehicle but still affect how the vehicle accomplishes its task by observing or interfering with the actions of the vehicle. Vulnerable road users (VRU) are considered one example of the bystander humans interfering with the autonomous vehicle. According to a recent research study, intent understanding between vulnerable road users and autonomous vehicles was one of the most critical signs that accounted for a trusted interaction between the two entities. In this paper we are proposing a computation framework for modeling trust between vulnerable road users and autonomous vehicles based on a shared intent understanding between the two of them.
机译：在人车交互领域的许多近期研究项目正在解决自动驾驶汽车中人与人之间的信任问题。几乎所有这些工作都集中在调查影响人类对这些车辆的信任的属性和因素。然而，关于旁观者对自动驾驶汽车的信任已经进行了一些研究。在自动驾驶汽车的背景下，旁观者是指不会明确地与自动驾驶汽车互动，但仍会通过观察或干扰汽车的动作来影响汽车如何完成其​​任务的人类。弱势道路使用者（VRU）被认为是旁观者干扰自动驾驶车辆的一个例子。根据最近的一项研究，脆弱的道路使用者和自动驾驶汽车之间的意图理解是导致这两个实体之间相互信任的最重要标志之一。在本文中，我们提出了一个计算框架，用于基于易受攻击的道路用户和自动驾驶汽车之间的共享意图理解对信任进行建模。

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