PhD, Professor
Department of Kinesiology and Phys. Ed. Wilfrid Laurier University
Biography
Dr. Michael Cinelli is a professor in the Department of Kinesiology & Physical Education at Wilfrid Laurier University. Dr. Cinelli completed a postdoctoral fellowship at Brown University’s Virtual Environment and Navigation Lab, studying goal-directed locomotion, and earned his PhD in kinesiology from the University of Waterloo with a specialization in behavioural and cognitive neural science. Since joining Laurier in 2008, his NSERC-funded research program has explored how visual information, dynamic stability, and perception interact to influence collision avoidance and adaptive locomotion in different environments across the lifespan.
Abstract
Navigating safely through a cluttered environment requires avoiding static and moving obstacles and, more specifically, other pedestrians. Fortunately, collisions between pedestrians or other objects rarely occur. This is due to a key role that vision plays in safely and efficiently guiding our routes away from collisions and towards open spaces. Visual information about an environment is gathered through eye movements allowing individuals to act appropriately (i.e., change speed, direction, or foot placement) in response to obstacles. However, the manner in which specific optical variables (from vision) are used to control actions and safely avoid collisions with environmental objects are unknown. Fundamentally there are differences between stationary and moving objects as well as between human and non-human obstacles. Therefore, it is critical to understand how actions differ when avoiding another person compared to a non-human object (stationary or moving). The focus of my research program is to determine what factors affect one’s decision-making capabilities when avoiding a collision with other pedestrians in different environments. My research has assessed both person-specific (i.e., size) and situation-specific (moving or stationary) characteristics of obstacles on avoidance behaviours in both real-world and virtual reality environments. Ultimately, my research will lead to understanding the behavioural variables that control locomotion in cluttered environments, which can be used to develop robots to safely navigate unfamiliar environments, create better crowd simulation models, or design urban spaces to allow safe pedestrian traffic.