On the quantum mechanics of optic flow and its application to driving in uncertain environments

Abstract The quantum mechanics approach is applied to the analysis of optic flow as a computational judgement model in order to develop a better understanding of car driver behaviour. It is argued that errors occur in the perception of distance, velocity and time because of a wave–image duality in the transfer of visual information and that this equates to fundamental uncertainty on the part of a driver between the variance in speed determination and foveal assignment. This quantum model, containing possibilities and probabilities, is contrasted to the ecological optic approach, which follows a classical view of deterministic assignments of information to trajectories from differentials in textural elements and gradients. Quantum mechanics can explain the occurrence of a number of motion-related perceptual phenomena. This includes the occlusion of images; driver fatigue; high speed adaptation and visual after-effect of motion; and the `white box' effect, where for an indifferent driver, limited illumination from night driving can increase speed and the underestimation of speed. These cases appear to happen when focus is bound to the road and the psychophysical energy of motion is discretely assigned beyond the retina. An ecological optic type approach may still be appropriate for low speed unbound vision in an energy continuum, where the peripheral field contains all the information for self-displacement assessment. Such modelling of the causes in the variance of driver behaviour has major implications for increasing driver safety and reducing road trauma.

[1]  Leonard Evans,et al.  Speed Estimation from a Moving Automobile , 1970 .

[2]  H. Ross,et al.  Optic-Flow and Cognitive Factors in Time-to-Collision Estimates , 1983, Perception.

[3]  H. Rachlin Scaling subjective velocity, distance, and duration , 1966 .

[4]  T J Triggs,et al.  Estimation of Automobile Speed under Day and Night Conditions , 1982, Human factors.

[5]  J. Gibson,et al.  A theoretical field-analysis of automobile-driving , 1938 .

[6]  S Salvatore,et al.  The Estimation of Vehicular Velocity as a Function of Visual Stimulation , 1968, Human factors.

[7]  R. Penrose The emperor's new mind: concerning computers, minds, and the laws of physics , 1989 .

[8]  Lee Dn,et al.  The optic flow field: the foundation of vision. , 1980 .

[9]  Lena Nilsson,et al.  EFFECTS OF A VISION ENHANCEMENT SYSTEM ON DRIVERS' ABILITY TO DRIVE SAFELY IN FOG. , 1996 .

[10]  R. Baker On Travel Behaviour Relative to a General Place Utility Field , 1994 .

[11]  J. Fodor The Modularity of mind. An essay on faculty psychology , 1986 .

[12]  Lisbeth Harms The influence of sight distance on subjects' lateral control: a study of simulated driving in fog , 1993 .

[13]  M. R Rodriguez,et al.  Quantal processing of visual information in the brain , 1998, Neuroscience.

[14]  Magnitude estimation of visual velocity. , 1972, The Journal of psychology.

[15]  J Tiffin,et al.  Distortion of drivers' estimates of automobile speed as a function of speed adaptation. , 1969, The Journal of applied psychology.

[16]  Hiroo Ohta,et al.  SPEED PERCEPTION IN DRIVING -- COMPARISON WITH TV OBSERVATION. , 1991 .

[17]  T. Miura,et al.  Behavior Oriented Vision: Functional Field of View and Processing Resources , 1987 .

[18]  G G Denton The Influence of Visual Pattern on Perceived Speed , 1980, Perception.

[19]  E Tenkink Lane keeping and speed choice with restricted sight distances , 1988 .

[20]  D Regan,et al.  How do we avoid confounding the direction we are looking and the direction we are moving? , 1982, Science.

[21]  V Cavallo,et al.  Visual Information and Skill Level in Time-To-Collision Estimation , 1988, Perception.

[22]  M Abram Judgments of speed on the open highway. , 1958 .

[23]  W. Edwards The theory of decision making. , 1954, Psychological bulletin.

[24]  J. T. Reason,et al.  Man in motion: The psychology of travel , 1974 .

[25]  Daniel Mestre,et al.  Rotation and Translation of Vehicles: Some Aspects of Their Dissociation , 1988 .

[26]  H. C. Longuet-Higgins,et al.  The interpretation of a moving retinal image , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[27]  H. Holland The Spiral After-Effect , 1966 .

[28]  D. Regan,et al.  Illusory motion in depth: Aftereffect of adaptation to changing size , 1978, Vision Research.

[29]  Will Spijkers,et al.  STREET ENVIRONMENT, DRIVING SPEED AND FIELD OF VISION. , 1991 .

[30]  D Solomon,et al.  Accidents on main rural highways related to speed, driver, and vehicle , 1964 .

[31]  J. Drösler The psychophysical function of binocular space perception , 1988 .

[32]  A. Beiser,et al.  Perspectives of Modern Physics , 1969 .

[33]  D. Stewart DRIVER PERCEPTUAL ERROR AND CHILD PEDESTRIAN ACCIDENTS. , 1991 .

[34]  Matthijs J. Koornstra SAFETY RELEVANCE OF VISION RESEARCH AND THEORY , 1993 .

[35]  H. Scherer,et al.  The influence of vestibular disorder on driving behaviour , 1996 .

[36]  R. Luce,et al.  On the possible psychophysical laws. , 1959, Psychological review.

[37]  D. Griffiths,et al.  Introduction to Quantum Mechanics , 1960 .

[38]  J. Sutherland The Quark and the Jaguar , 1994 .

[39]  R. G. D. Allen,et al.  The Foundations of a Mathematical Theory of Exchange , 1932 .

[40]  Leonard Evans Automobile-Speed Estimation Using Movie-film Simulation , 1970 .

[41]  S. Hecht,et al.  ENERGY, QUANTA, AND VISION , 1942, The Journal of general physiology.

[42]  D. Baylor,et al.  Responses of retinal rods to single photons. , 1979, The Journal of physiology.

[43]  Manfred Hess,et al.  THE DEPENDENCY OF DRIVERS' VIEWING BEHAVIOUR ON SPEED AND STREET ENVIRONMENT STRUCTURE. , 1991 .