Optic flow asymmetries bias high-speed steering along roads

Abstract

How do animals and insects use visual information to move through the world successfully? Optic flow, the pattern of motion at the eye, is a powerful source of information about self-motion. Insects and humans are sensitive to the global pattern of optic flow and try to maintain flow symmetry when flying or walking. The environments humans encounter, however, often contain demarcated paths that constrain future trajectories (e.g., roads), and steering has been successfully modeled using only road edge information. Here we examine whether flow asymmetries from a textured ground plane influences humans steering along demarcated paths. Using a virtual reality simulator we observed that different textures on either side of the path caused predictable biases to steering trajectories, consistent with participants reducing flow asymmetries. We also generated conditions where one textured region had no flow (either the texture was removed or the textured region was static). Despite the presence of visible path information, participants were biased toward the no-flow region consistent with reducing flow asymmetries. We conclude that optic flow asymmetries can lead to biased locomotor steering even when traveling along demarcated paths.

Steering bends and changing lanes: The impact of optic flow and road edges on two point steering control

“…Using Land and Horwood's (1995) method of adjusting 18 vertical viewing ''windows'' (a small segment where both road edges were visible, and outside of which road edges were invisible), Chatziastros et al (1999) found that adding road texture (i.e., optic flow information) reduced lateral deviation uniformly across all viewing segment conditions. Indeed, humans appear to use optic flow as a control source even when current and future steering requirements are specified by visible road-edges (Kountouriotis et al, 2013;Kountouriotis et al, 2016;Mole et al, 2016). Kountouriotis et al (2013) demonstrated that placing different textures either side of the road caused predictable biases to steering trajectories.…”

“…Indeed, humans appear to use optic flow as a control source even when current and future steering requirements are specified by visible road-edges (Kountouriotis et al, 2013;Kountouriotis et al, 2016;Mole et al, 2016). Kountouriotis et al (2013) demonstrated that placing different textures either side of the road caused predictable biases to steering trajectories. Most strikingly if one region was left untextured or kept static (and so created a region that produced no optic flow), participants were biased toward the ''no-flow'' region despite the presence of visible road-edges.…”

A GPU-accelerated cortical neural network model for visually guided robot navigation

“…For 244 example, honeybees use this control law to steer collision-free paths through even narrow 245 gaps by balancing the apparent speeds of motion of the images in their eyes (Srinivasan & 246 Zhang, 1997). Interestingly, there is also some evidence for the Balance Strategy in 247 humans (Kountouriotis, et al, 2013).However, the present model differs in an important 248 way from the traditional Balance Strategy, in that it tries to balance the flow generated 249 from motion discontinuities in the visual field, which are thought to correspond to 250 obstacles in the scene, instead of balancing a conventional optic flow field. For more 251 information see Section "Neurophysiological evidence and model alternatives".…”

“…Optic flow tends to dominate 545 when there is sufficient visual surface structure in the scene (Li & Warren, 2000; Warren, 546 et al, 2001; Wilkie & Wann, 2003), whereas egocentric direction dominates when visual 547 structure is reduced (Rushton, et al, 1998; Rushton, Wen, & Allison, 2002). Interestingly, 548 optic flow asymmetries are able to systematically bias the steering of human subjects,even 549in the presence of explicit path information(Kountouriotis, et al, 2013). This finding may 550 hint at the possibility of a cortical analog to the Balance Strategy(Duchon & Warren, 2002; 551…”

Sensorimotor basis of motor vehicle control

“…Since Gibson (Gibson 1950, Gibson 1958) first introduced the concept of optic flow, many follow-up studies have served to confirm that optic flow plays an important role in human locomotion (Warren and Hannon 1988, Warren and Hannon 1990, Hildreth 1992, Van den Berg 1993, Banks, Ehrlich et al 1996, Ehrlich, Beck et al 1998, Lappe, Bremmer et al 1999, Warren, Kay et al 2001, Wilkie and Wann 2002, Wilkie and Wann 2003, Li, Stone et al 2011, Kountouriotis, Shire et al 2013, Li and Niehorster 2014. It is currently generally believed that with sufficient optic flow and extra-retinal information (i.e.…”