Collaborative Research: Decision Processes in Human Navigation

成功地从一个地方导航到另一个地方可能需要做出艰难的决定。 我们经常需要考虑可能路线的成本和收益。 例如，市中心建筑物之间的最佳步行路径可能是天气宜人时的短户外路径，或者在太热或太冷的月份通过室内通道的较长路径。 我们还利用我们的知识来决定在哪里搜索我们需要的东西。 有经验的司机知道，例如，一个带购物中心是一个更好的地方找到一个加油站比是一个住宅区。 我们可能还需要决定我们是否足够了解一个环境，以依赖我们的记忆和方向感，或者应该使用手机上的地图应用程序。 为了做出正确的选择，避免迷失方向，我们需要依靠几个信息来源。一个重要的来源是我们所看到的，如道路，小径和熟悉的地方。 另一个重要的来源来自我们的身体：当我们走路和转弯时，即使闭上眼睛，我们也能感觉到我们走了多远，我们面对的是哪个方向。 这些信息来源告诉我们我们在哪里，我们要去哪里，以及到达那里有多难（例如，爬陡峭的山vs.绕着它走）。 这项研究调查了人们如何做出这类决定，如何处理相互冲突的信息来源（例如，我们的方向感指示我们应该左转但熟悉的地标指示我们应该右转），并使用导航辅助设备（例如，环境的俯视图）。 研究人员将使用人们选择和行动的数学模型来了解人类大脑如何存储和使用空间知识进行导航。 这些结果可以为技术的使用提供信息，从视频游戏的移动界面到支持GPS的地图。研究人员探索了导航决策和行动受以下因素影响的方式：（a）关于导航员位置和目标位置的空间线索（例如，环境中的地标，来自行走和转弯的基于身体的提示），（B）与可能的选择相关联的成本（例如，努力、时间），以及（c）导航器的个体特性（例如，空间能力、风险承受能力）。实验使用沉浸式虚拟现实来保持对视觉场景的严格控制，同时允许在导航过程中进行完全的物理运动;这项技术允许导航员在虚拟环境中行走和转弯，就像他们在真实的世界中一样。这些实验研究了：1）当这些线索相互不一致时，导航员如何使用来自多个空间线索的信息来找到目标; 2）导航员如何考虑导航成本，例如在深沙中的短路径或坚实地面上的较长路径之间进行选择; 3）导航员如何使用先验知识来做出导航决策，例如当在不熟悉的城市中选择最有可能搜索餐馆的地方时，知道餐馆更可能位于商业区而不是住宅区;以及4）导航器如何将来自技术的空间信息（例如由GPS启用的地图提供的空间信息）与由视觉和身体运动提供的自然线索结合联合收割机。 参与人类导航的认知过程的计算模型将用于扩展人类决策和行动的解释性理论。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

Navigating successfully from one place to another can require difficult decisions. We often need to consider the costs and the benefits of possible routes. For example, the best walking path between downtown buildings may be a short outdoor path when the weather is pleasant or a longer path through indoor passageways during overly hot or cold months. We also use our knowledge to make decisions about where to search for something that we need. Experienced drivers know, for example, that a strip mall is a better place to find a gas station than is a residential neighborhood. We also may need to decide whether we know an environment well enough to rely on our memories and sense of direction or should use the mapping app on our cell phones. To make good choices and to keep from getting lost, we need to rely on several sources of information. One important source is what we see, such as roads, trails, and familiar places. Another important source is from our bodies: As we walk and turn, even with our eyes closed, we have a sense of how far we have traveled and which directions we are facing. These sources of information tell us where we are, where we are headed, and how hard it will be to get there (e.g., climbing a steep hill vs. walking around it). This research investigates how people make these sorts of decisions, deal with conflicting sources of information (e.g., our sense of direction indicates that we should turn left but a familiar landmark indicates that we should turn right), and use navigation aids (e.g., an overhead map of the environment). The investigators will use mathematical models of people’s choices and actions to understand how the human brain stores and uses spatial knowledge for navigation. The results can inform the use of technology, ranging from movement interfaces for video games to GPS-enabled maps. The investigators explore the ways in which navigational decisions and actions are affected by (a) spatial cues about the navigator’s location and the goal location (e.g., landmarks in the environment, body-based cues from walking and turning), (b) costs associated with possible choices (e.g., effort, time), and (c) individual characteristics of the navigator (e.g., spatial ability, risk tolerance). Experiments use immersive virtual reality to maintain tight control over the visual scene while allowing for full physical movement during navigation; this technology allows navigators to walk and turn in virtual environments just as they do in the real world. The experiments examine 1) how navigators use information from multiple spatial cues to find a goal when those cues are inconsistent with one another; 2) how navigators account for navigational costs, as when choosing between a short path through deep sand or a longer path on firm ground; 3) how navigators use prior knowledge to make navigational decisions, as when selecting the most likely place to search for a restaurant within an unfamiliar city, knowing that a restaurant is more likely to be located in a business district than a residential neighborhood; and 4) how navigators combine spatial information from technology, such as that provided by a GPS-enabled map, with natural cues provided by vision and bodily movement. Computational models of the cognitive processes involved in human navigation will be used to expand explanatory theories of human decisions and actions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.