Literature DB >> 15784200

Towards a general theory of driver behaviour.

Ray Fuller1.   

Abstract

Taylor [Taylor, D.H., 1964. Drivers' galvanic skin response and the risk of accident. Ergonomics 7, 439-451] argued that drivers attempt to maintain a constant level of anxiety when driving which Wilde [Wilde, G.J.S., 1982. The theory of risk homeostasis: implications for safety and health. Risk Anal. 2, 209-225] interpreted to be coupled to subjective estimates of the probability of collision. This theoretical paper argues that what drivers attempt to maintain is a level of task difficulty. Naatanen and Summala [Naatanen, R., Summala, H., 1976. Road User Behaviour and Traffic Accidents. North Holland/Elsevier, Amsterdam, New York] similarly rejected the concept of statistical risk as a determinant of driver behaviour, but in so doing fell back on the learning process to generate a largely automatised selection of appropriate safety margins. However it is argued here that driver behaviour cannot be acquired and executed principally in such S-R terms. The concept of task difficulty is elaborated within the framework of the task-capability interface (TCI) model, which describes the dynamic interaction between the determinants of task demand and driver capability. It is this interaction which produces different levels of task difficulty. Implications of the model are discussed regarding variation in performance, resource allocation, hierarchical decision-making and the interdependence of demand and capability. Task difficulty homeostasis is proposed as a key sub-goal in driving and speed choice is argued to be the primary solution to the problem of keeping task difficulty within selected boundaries. The relationship between task difficulty and mental workload and calibration is clarified. Evidence is cited in support of the TCI model, which clearly distinguishes task difficulty from estimates of statistical risk. However, contrary to expectation, ratings of perceived risk depart from ratings of statistical risk but track difficulty ratings almost perfectly. It now appears that feelings of risk may inform driver decision making, as Taylor originally suggested, but not in terms of risk of collision, but rather in terms of task difficulty. Finally risk homeostasis is presented as a special case of task difficulty homeostasis.

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Mesh:

Year:  2005        PMID: 15784200     DOI: 10.1016/j.aap.2004.11.003

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  24 in total

1.  Variations on a theme: Topic modeling of naturalistic driving data.

Authors:  Elease McLaurin; Anthony D McDonald; John D Lee; Nazan Aksan; Jeffrey Dawson; Jon Tippin; Matthew Rizzo
Journal:  Proc Hum Factors Ergon Soc Annu Meet       Date:  2014-09

2.  Factors affecting return to driving post-stroke.

Authors:  K M Tan; A O'Driscoll; D O'Neill
Journal:  Ir J Med Sci       Date:  2010-07-28       Impact factor: 1.568

3.  Predicting road test performance in adults with cognitive or visual impairment referred to a Veterans Affairs Medical Center driving clinic.

Authors:  Patricia M Niewoehner; Rochelle R Henderson; Jami Dalchow; Tracy L Beardsley; Robert A Stern; David B Carr
Journal:  J Am Geriatr Soc       Date:  2012-10-30       Impact factor: 5.562

4.  Do older drivers at-risk for crashes modify their driving over time?

Authors:  Lesley A Ross; Olivio J Clay; Jerri D Edwards; Karlene K Ball; Virginia G Wadley; David E Vance; Gayla M Cissell; Daniel L Roenker; John J Joyce
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2009-02-04       Impact factor: 4.077

5.  What you may not see might slow you down anyway: masked images and driving.

Authors:  Ben Lewis-Evans; Dick de Waard; Jacob Jolij; Karel A Brookhuis
Journal:  PLoS One       Date:  2012-01-18       Impact factor: 3.240

6.  Systematic screening for unsafe driving due to medical conditions: still debatable.

Authors:  Sandy Leproust; Emmanuel Lagarde; L Rachid Salmi
Journal:  BMC Public Health       Date:  2008-01-23       Impact factor: 3.295

7.  Reading text while driving: understanding drivers' strategic and tactical adaptation to distraction.

Authors:  Yulan Liang; William J Horrey; Joshua D Hoffman
Journal:  Hum Factors       Date:  2014-08-07       Impact factor: 2.888

8.  Texting at the light and other forms of device distraction behind the wheel.

Authors:  James J Bernstein; Joseph Bernstein
Journal:  BMC Public Health       Date:  2015-09-26       Impact factor: 3.295

9.  Driving cessation and dementia: results of the prospective registry on dementia in Austria (PRODEM).

Authors:  Stephan Seiler; Helena Schmidt; Anita Lechner; Thomas Benke; Guenter Sanin; Gerhard Ransmayr; Riccarda Lehner; Peter Dal-Bianco; Peter Santer; Patricia Linortner; Christian Eggers; Bernhard Haider; Margarete Uranues; Josef Marksteiner; Friedrich Leblhuber; Peter Kapeller; Christian Bancher; Reinhold Schmidt
Journal:  PLoS One       Date:  2012-12-26       Impact factor: 3.240

10.  Classifying visuomotor workload in a driving simulator using subject specific spatial brain patterns.

Authors:  Chris Dijksterhuis; Dick de Waard; Karel A Brookhuis; Ben L J M Mulder; Ritske de Jong
Journal:  Front Neurosci       Date:  2013-08-21       Impact factor: 4.677

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