Control of visually guided braking using constant- $$\tau$$ and proportional rate

Springer Science and Business Media LLC - Tập 239 - Trang 217-235 - 2020
Didem Kadihasanoglu1,2, Randall D. Beer1, Ned Bingham3,4, Geoffrey P. Bingham1,5
1Cognitive Science Program, Indiana University, Bloomington, USA
2Department of Psychology, TOBB University of Economics and Technology, Ankara, Turkey
3Electrical and Computer Engineering, Cornell University, Ithaca, USA
4Department of Computer Engineering, Yale University, New Haven, USA
5Department of Psychological and Brain Sciences, Indiana University, Bloomington, USA

Tóm tắt

This study investigated the optical information and control strategies used in visually guided braking. In such tasks, drivers exhibit two different braking behaviors: impulsive braking and continuously regulated braking. We designed two experiments involving a simulated braking task to investigate these two behaviors. Participants viewed computer displays simulating an approach along a linear path over a textured ground surface toward a set of road signs. The task was to use a joystick as a brake to stop as close as possible to the road signs. Our results showed that participants relied on a weak constant- $$\tau$$ strategy (Bingham 1995) when regulating the brake impulsively. They used discrete $$\tau$$ values as critical values and they regulated the brake so as not to let $$\tau$$ fall below these values. Our results also showed that proportional rate control (Anderson and Bingham 2010, 2011) is used in continuously regulated braking. Participants initiated braking at a certain proportional rate value and controlled braking so as to maintain that value constant during the approach. Proportional rate control is robust because the value can fluctuate within a range to yield good performance. We argue that proportional rate control unifies the information-based approach and affordance-based approach to visually guided braking.

Tài liệu tham khảo

Anderson J, Bingham GP (2010) A solution to the online guidance problem for targeted reaches: proportional rate control using relative disparity τ. Exp Brain Res 205:291–306 Anderson J, Bingham GP (2011) Locomoting-to-reach: information variables and control strategies for nested actions. Exp Brain Res 214(4):631–644 Bingham GP (1995) The role of perception in timing: Feedback control in motor programming and task dynamics. In: Covey E, Hawkins H, McMullen T, Port R (eds) Neural representation of temporal patterns. Plenum Press, New York, pp 129–157 Cavallo V, Laurent M (1988) Visual information and skill level in time-to-collision estimation. Perception 17:623–632 Dixon PM, Saint-Maurice PF, Kim Y, Hibbing P, Bai Y, Welk GJ (2018) A primer on the use of equivalence testing for evaluating measurement agreement. Med Sci Sports Exerc 50(4):837 Fajen BR (2005a) Calibration, information, and control strategies for braking to avoid a collision. J Exp Psychol Hum Percept Perform 31(3):480–501 Fajen BR (2005b) Perceiving possibilities for action: On the necessity of calibration and perceptual learning for the visual guidance of action. Perception 34(6):741–755 Fajen BR (2005c) The scaling of information to action in visually guided braking. J Exp Psychol Hum Percept Perform 31(5):1107–1123 Fajen BR (2007) Affordance-based control of visually guided action. Ecol Psychol 19(4):383–410 Fath A, Marks B, Bingham GP (2013) Response to perturbation in constant tau-dot versus constant proportional rate models of visually guided braking. Journal of Vision 3:747. https://doi.org/10.1167/13.9.747 Fath A, Marks B, Snapp-Childs W, Bingham GP (2014) Information and control strategy to solve the degrees of freedom problem for nested locomotion-to-reach. Exp Brain Res 232:3821–3831. https://doi.org/10.1007/s00221-014-4072-0 Gibson JJ (1979/1986) The ecological approach to visual perception. Boston, MA: Houghton Mifflin. Harrison HS, Turvey MT, Frank TD (2016) Affordance-based perception-action dynamics: a model of visually guided braking. Psychol Rev 123:305–323 Kadihasanoglu D, Beer RD, Bingham GP (2015) Evolutionary robotics techniques used to model information and control of visually-guided braking. Adaptive Behavior 23(3):125–142 Kim NG, Turvey MT, Carello C (1993) Optical information about the severity of upcoming contacts. J Exp Psychol Hum Percept Perform 19:179–193 Larish JF, Flach JM (1990) Sources of information useful for perception of speed of rectilinear self-motion. J Exp Psychol Hum Percept Perform 16:295–302 Lee DN (1976) A theory of visual control of braking based on information about time-to-collision. Perception 5:437–459 Regan D, Hamstra SJ (1993) Dissociation of discrimination thresholds for time to contact and for rate of angular expansion. Vision Res 33(4):447–462 Todd JT (1981) Visual information about moving objects. J Exp Psychol Hum Percept Perform 7:795–810 Walker E, Nowacki AS (2011) Understanding equivalence and noninferiority testing. J Gen Intern Med 26(2):192–196 Yilmaz EH, Warren WH Jr (1995) Visual control of braking: A test of the τ hypothesis. J Exp Psychol Hum Percept Perform 21:996–1014