A Synthetic-Vision Based Steering Approach for Crowd Simulation
A Synthetic-Vision Based Steering Approach for Crowd Simulation
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DOI：
10.1145/1778765.1778860
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发表时间：
2010-07-01
影响因子：
6.2
通讯作者：
Donikian, Stephane
中科院分区：
文献类型：
--
作者：
Ondrej, Jan;Pettre, Julien;Donikian, Stephane
在日常的运动控制中，人类依靠感知环境的光流来实现无碰撞导航。在人群中，尽管由无数障碍物组成的环境非常复杂，但人类表现出了非凡的避碰能力。认知科学对人类运动的研究表明，从视流中提取相对简洁的信息，以实现安全的运动。本文针对交互式人群模拟的要求，探索了一种新的基于视觉的步行者间避碰方法。通过基于认知科学的结果模拟人类，我们可以检测未来的碰撞以及视觉刺激的危险程度。马达的反应是双重的：重新定位策略防止未来的碰撞，而减速策略防止即将发生的碰撞。我们的模拟结果的几个例子表明，使用我们的方法加强了步行者自组织模式的出现。这些新出现的现象在视觉上很吸引人。更重要的是，它们提高了步行者的整体交通效率，并避免了不太可能的锁定情况。
In the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states that relatively succinct information is extracted from the optic flow to achieve safe locomotion. In this paper, we explore a novel vision-based approach of collision avoidance between walkers that fits the requirements of interactive crowd simulation. By simulating humans based on cognitive science results, we detect future collisions as well as the level of danger from visual stimuli. The motor-response is twofold: a reorientation strategy prevents future collision, whereas a deceleration strategy prevents imminent collisions. Several examples of our simulation results show that the emergence of self-organized patterns of walkers is reinforced using our approach. The emergent phenomena are visually appealing. More importantly, they improve the overall efficiency of the walkers' traffic and avoid improbable locking situations.