A vision-based model of locomotion in crowded environments

当人们走在繁忙的人行道上时，每天都会在自然环境中面临复杂的交通挑战， 穿过拥挤的火车站，或在购物中心。为了引导运动，视觉系统通过物体和其他行人的不断演变的布局来检测关于自我运动的信息，并生成安全的 和高效的出行路径。视力低下的人报告说，行动能力是最困难的活动之一 日常生活，特别是在人群中行走或使用公共交通工具，碰撞风险增加， 受伤，并降低了独立性。然而，到目前为止，研究人员还不清楚视觉是如何在如此复杂的日常环境中控制运动行为的。 该项目的长期目标是开发第一个在动态、拥挤环境中基于视觉的行人行为模型，并利用结果设计更有效的辅助技术。 大多数运动控制模型(来自机器人学、计算机动画和生物学)都采用3D位置 和环境物体的速度作为输入，并根据客观标准规划无碰撞路径。一个 基于视觉的模型将获取行人可以获得的光学信息，并生成与人类相似的信息 基于实验数据的运动路径。因此，第一个具体目标是确定有效的视觉 引导人们与人群同行的信息。具体地说，我们将测试这样的假设：(A)光流，(B)分割的2D运动，或(C)感知的3D运动，在多个邻居之后使用，以及该信息如何 在空间和时间上都是完整的。第二个具体目标是确定监管的视觉控制法则 在人群中行走的速度和方向。具体地说，我们将测试碰撞避免、跟随和超车的相互竞争的模型，并形式化基于视觉的行人模型。根据这些结果，第三个具体的 目的是评估运动指导中感觉替代的替代方法。具体地说，我们将基于对触觉图案中的有效光学变量进行重新编码来比较振动触觉带的编码方案， 或者使用基于视觉的模型通过定向提示来引导用户。 行为学实验将测试控制人群运动的光学变量和控制规律，通过 在身临其境的虚拟环境(12米x 14米)中行走时操纵视觉显示。基于代理的 模拟将比较实验数据和之前收集的人群数据的相互竞争的模型。 这种方法将使我们能够测试关于视觉信息和视觉控制的替代假设 法律，并创建一个实验基础上的基于视觉的行人模型。感觉替代实验将在匹配的视觉和触觉虚拟环境中测试正常视力的参与者；如果结果 有前景的，低视力和盲人参与者的测试将在后续的应用中进行。这个 研究将有助于在复杂、动态的环境中学习视觉引导移动的基本知识，并将其应用于辅助移动设备的设计。

People face complex mobility challenges in natural settings every day, when walking down a busy sidewalk, through a crowded train station, or in a shopping mall. To guide locomotion, the visual system detects information about self-motion through an evolving layout of objects and other pedestrians, and generates a safe and efficient path of travel. Individuals with low vision report mobility as one of the most difficult activities of daily living, particularly walking in crowds or using public transportation, with increased risks of collision, injury, and reduced independence. As yet, however, researchers do not understand how vision is used to control locomotor behavior in such complex, everyday settings. The long-term objective of the proposed project is to develop the first vision-based model of pedestrian behavior in dynamic, crowded environments, and use the results to design more effective assistive technology. Most models of locomotor control (from robotics, computer animation, and biology) assume the 3D positions and velocities of environmental objects as input, and plan a collision-free path according to objective criteria. A vision-based model would take the optical information available to a pedestrian and generate human-like paths of locomotion, based on experimental data. The first specific aim is thus to determine the effective visual information that guides walking with a crowd. Specifically, we will test the hypotheses that (a) optic flow, (b) segmented 2D motion, or (c) perceived 3D motion, is used follow multiple neighbors, and how this information is spatially and temporally integrated. The second specific aim is to determine the visual control laws that regulate walking speed and direction in a crowd. Specifically, we will test competing models of collision avoidance, following, and overtaking, and formalize a vision-based pedestrian model. Based on these results, the third specific aim is to evaluate alternative approaches to sensory substitution for locomotor guidance. Specifically, we will compare coding schemes for a vibrotactile belt based on recoding the effective optical variables in tactile patterns, or using the vision-based model to steer the user with directional cuing. Behavioral experiments will test the optical variables and control laws that govern locomotion in crowds, by manipulating visual displays during walking in an immersive virtual environment (12m x 14m). Agent-based simulations will compare competing models of the experimental data and previously collected crowd data. This methodology will enable us to test alternative hypotheses about visual information and visual control laws, and create an experimentally-grounded vision-based pedestrian model. Sensory substitution experiments will test normally-sighted participants in matched visual and tactile virtual environments; if the results are promising, tests with low-vision and blind participants will be pursued in subsequent applications. The research will contribute to basic knowledge about visually-guided locomotion in complex, dynamic environments, and apply it to the design of an assistive mobility device.