How Football Players Determine where to Run to Tackle other Players: A Mathematical and Psychological Description and Analysis

Shaffer, Dennis M.; Gregory, Thomas B.

doi:10.2174/1875399x00902010029

Cited by 8 publications

(9 citation statements)

References 29 publications

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“…Similarly, moving obstacles can be avoided by moving so as to ensure that the bearing angle does not remain fixed. Numerous studies on humans and other animals (including bats, dragonflies, and fish) suggest that the bearing angle is used to guide interception and obstacle avoidance [24], [25], [26], [27], [28], [29], [30], [31].…”

Section: Discussionmentioning

confidence: 99%

Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion

Fajen

Matthis

2013

PLoS ONE

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Many locomotor tasks involve interactions with moving objects. When observer (i.e., self-)motion is accompanied by object motion, the optic flow field includes a component due to self-motion and a component due to object motion. For moving observers to perceive the movement of other objects relative to the stationary environment, the visual system could recover the object-motion component – that is, it could factor out the influence of self-motion. In principle, this could be achieved using visual self-motion information, non-visual self-motion information, or a combination of both. In this study, we report evidence that visual information about the speed (Experiment 1) and direction (Experiment 2) of self-motion plays a role in recovering the object-motion component even when non-visual self-motion information is also available. However, the magnitude of the effect was less than one would expect if subjects relied entirely on visual self-motion information. Taken together with previous studies, we conclude that when self-motion is real and actively generated, both visual and non-visual self-motion information contribute to the perception of object motion. We also consider the possible role of this process in visually guided interception and avoidance of moving objects.

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Section: Discussionmentioning

confidence: 99%

Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion

Fajen

Matthis

2013

PLoS ONE

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“…The BA model is widely used to account for collision detection, interception, and obstacle avoidance in both humans (Cutting et al, 1995; Lenoir et al, 1999, 2002; Chardenon et al, 2004; Fajen and Warren, 2004; Ni and Andersen, 2008; Shaffer and Gregory, 2009) and non-human animals (Lanchester and Mark, 1975; Olberg et al, 2000; Ghose et al, 2006). In addition, the behavioral dynamics model (Fajen and Warren, 2003; Warren, 2006), which is one of the few general models of visually guided locomotion in humans, implements the BA strategy in its moving target (Fajen and Warren, 2007) and moving obstacle (Cohen et al, 2006) components.…”

Section: The Bearing Angle Modelmentioning

confidence: 99%

Guiding locomotion in complex, dynamic environments

Fajen¹

2013

Front. Behav. Neurosci.

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Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects—that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach.

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“…For a target headed off to the side at a relatively constant velocity, another control strategy that can be used to achieve interception is to maintain a CEA, or in other words, to keep moving in a direction that bears ahead of the target by a constant angle (Bastin & Montagne, 2005;Chardenon, Montagne, Buekers, & Laurent, 2002;Pollack, 1995;Rushton & Allison, 2013;Shaffer & Gregory, 2009). Maintenance of this angular constancy guarantees that a fielder will converge upon any target that the fielder can keep up with in the lateral direction.…”

Section: Constant Eccentricity Anglementioning

confidence: 99%

Optical angular constancy is maintained as a navigational control strategy when pursuing robots moving along complex pathways

2015

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The optical navigational control strategy used to intercept moving targets was explored using a real-world object that travels along complex, evasive pathways. Fielders ran across a gymnasium attempting to catch a moving robot that varied in speed and direction, while ongoing position was measured using an infrared motion-capture system. Fielder running paths were compared with the predictions of three lateral control models, each based on maintaining a particular optical angle relative to the robotic target: (a) constant alignment angle (CAA), (b) constant eccentricity angle (CEA), and (c) linear optical trajectory (LOT). Findings reveal that running pathways were most consistent with maintenance of LOT and least consistent with CEA. This supports that fielders use the same optical control strategy of maintaining angular constancy using a LOT when navigating toward targets moving along complex pathways as when intercepting simple ballistic trajectories. In those cases in which a target dramatically deviates from its optical path, fielders appear to simply reset LOT parameters using a new constant angle value. Maintenance of such optical angular constancy has now been shown to work well with ballistic, complex, and evasive moving targets, confirming the LOT strategy as a robust, general-purpose optical control mechanism for navigating to intercept catchable targets, both airborne and ground based.

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How Football Players Determine where to Run to Tackle other Players: A Mathematical and Psychological Description and Analysis

Cited by 8 publications

References 29 publications

Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion

Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion

Guiding locomotion in complex, dynamic environments

Optical angular constancy is maintained as a navigational control strategy when pursuing robots moving along complex pathways

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