Mechanisms of Visual Information Acquisition in Driving

驾驶视觉信息获取机制

• 批准号: RGPIN-2021-02730
• 负责人: Wolfe, Benjamin
• 金额: $ 2.04万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764202
• 关键词: Mechanisms; Visual; Information; Acquisition; Driving

Imagine you are driving down the street, and someone steps into the road ahead of you without looking to see if you have seen them - how quickly can you understand that the situation has changed? What do you need to know to stop in time, and how do you learn what you need to know about the situation in time to avoid a crash? What does your car need to know about what you know, and how can knowing all of this make the road safer for everyone? Right now, there is a push for more self-driving features in cars, but doing this safely means that we have to understand the person in the driver's seat more completely than we do. If, for example, your car is driving you to work, but encounters a situation it cannot handle and asks you to take over, what does it take for you to understand what is going on, much less to avoid the moose that just stepped into the road? Fundamentally, this is a question of human visual perception more than it is a question of engineering: how do drivers understand dynamic, real-world situations, like the road ahead of them? Drivers do not have time to look at everything in the world before events overtake them, so how do they get the information they need when they need it, how do they learn to do this, and how do their abilities change as they age? We can look at a photo of a real-world scene and understand it in the blink of an eye, using information from across the entire image, not just where we are looking, but what do we do in real situations when everything is moving? How do we do this on the road, where objects move around us and we move through the world? Research on driver behavior talks about the concept of Situation Awareness, our awareness of our environment and what might happen, but does not ask how we get the information we need to develop this awareness. This proposal builds on my work on Information Acquisition, where I hypothesize that much of what we need to know about the world we acquire with peripheral vision, that is, from the rest of our field of view away from where we are looking now, and that we look at specific things or locations in the world only when we need more detail about something specific. In this proposal, I ask: 1)When do drivers need to look at particular things or locations when driving, and when does the rest of their visual field give them what they need? 2)How much information about our environment do drivers need and what can they do without? 3)How do drivers learn to balance our need for information with the tools they have to acquire it, and how does this change as we learn and age? Answers to these questions are critical for designing next-generation vehicles that account for what drivers can and cannot perceive, and developing this understanding will help us better understand how we perceive the world, and help make the road safer for everyone.

想象一下，你正在街上开车，有人走到你前面的路上，没有看你是否看到他们-你能多快明白情况已经改变了？你需要知道什么才能及时停下来，你如何及时了解你需要知道的情况，以避免撞车？你的车需要知道你所知道的什么，以及如何知道所有这些使道路对每个人都更安全？现在，人们正在推动汽车的自动驾驶功能，但安全地做到这一点意味着我们必须比我们更全面地了解驾驶员座位上的人。例如，如果你的车载你去上班，但遇到了它无法处理的情况，并要求你接管，你需要什么才能明白发生了什么，更不用说避开刚刚踏入道路的驼鹿了？从根本上说，这是一个人类视觉感知的问题，而不是一个工程问题：驾驶员如何理解动态的、真实的情况，比如他们前面的道路？司机没有时间在事情发生之前看世界上的一切，那么他们如何在需要的时候获得所需的信息，他们如何学习这样做，以及他们的能力如何随着年龄的增长而变化？我们可以看到一张真实世界场景的照片，并在眨眼之间理解它，使用整个图像的信息，不仅仅是我们所看的地方，而是当一切都在移动时，我们在真实的情况下该怎么做？在路上，物体在我们周围移动，我们在世界中移动，我们是如何做到这一点的？对驾驶员行为的研究讨论了情境意识的概念，我们对环境的意识以及可能发生的事情，但没有问我们如何获得发展这种意识所需的信息。这个建议建立在我的信息获取工作的基础上，在那里我假设我们需要知道的关于世界的大部分信息都是通过周边视觉获得的，也就是说，从我们现在所看的地方以外的其他视野中获得的，并且只有当我们需要关于特定事物的更多细节时，我们才会看到世界上的特定事物或位置。在这一提议中，我要求：1）驾驶员在驾驶时什么时候需要看特定的东西或位置，以及他们视野的其他部分什么时候给他们提供他们需要的东西？2)驾驶员需要多少关于我们环境的信息，没有这些信息他们能做什么？3)驾驶员如何学会平衡我们对信息的需求与他们获得信息的工具，以及随着我们的学习和年龄增长，这种平衡如何变化？这些问题的答案对于设计下一代汽车至关重要，这些汽车可以解释驾驶员可以感知和不能感知的东西，而发展这种理解将有助于我们更好地理解我们如何感知世界，并有助于使道路对每个人都更安全。