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DRIVABILITY: a new concept for modelling driving performance

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Abstract

Various types of driver models have been proposed in the literature, such as taxonomic, functional, and motivational. Recently, the promising Michon model was extended, leading to the widely used GADGET matrix. Nevertheless, the correlation of such models to actual road accidents and their causes has so far been weak. In addition, the use of those models for predicting driver behavioural adaptation has not proven feasible. This paper introduces a new concept for modelling driver's performance, that of DRIVABILITY. DRIVABILITY is defined as a combination of permanent and temporary factors that affect a driver's performance. Furthermore, this paper proposes a DRIVABILITY index and a methodology to measure it, in order to move from over-simplistic, hierarchical modelling to a multi-dimensional sphere. The usability of the newly proposed concept is shown through its application in three different example cases, including a system monitoring driver hypovigilance, a system for driver basic training, and an elderly driver's assessment scheme.

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References

  • Amditis A, Portouli V, Bekiaris A (2000) COMUNICAR traffic scenarios and environmental factors. Internal report TP_ICCS3_2_1 of COMUNICAR project, Institute of Communication and Computer Systems, Athens, Greece

  • Bekiaris E (2001) Methodology for traffic risk estimation of critical traffic scenarios. Internal report HIT4_1 of AWAKE project, Hellenic Institute of Transport, Thermi, Greece

  • Bekiaris E, Portouli E (1999) Emergency detection and handling strategies. Deliverable 4.1 of IN-ARTE project, TRD International S.A., Thessaloniki, Greece (TR4014)

  • Blomqvist G (1986) An utility maximization model of driver traffic safety behaviour. Accid Anal Prev 18:371–375

    Article  PubMed  Google Scholar 

  • Fuller R (1984) A conceptualisation of driving behaviour as threat avoidance. Ergonomics 27:1139–1135

    CAS  PubMed  Google Scholar 

  • Hakamies-Blomqvist L (1996) Research on older drivers, a review. IATSS Res 20(1):93–97

    Google Scholar 

  • Harms L (1991) Experimental studies of variations in cognitive load and driving speed in traffic and in driving simulation. In: Gale AG, Brown ID, Haslegrave CM, Smith P, Taylor SH (eds) Vision in vehicles, III. Elsevier/North-Holland, Amsterdam, pp 71–78

  • Hatakka M, Keskinen E, Gregersen NR, Glad A, Hernetkoski K (1999) Results of EU-project GADGET, Work package 3. In: Siegrist S (ed) Driver training, testing and licensing – towards theory based management of young drivers injury risk in road traffic". BFU report 40, Schweizerische Beratungsstelle für Unfallverhütung, Berne

  • Hoeschen A, Bekiaris E (2001) Inventory of driver training needs and major gaps in the relevant training procedures. TRAINER deliverable D2.1, Institut fuer Arbeitsorganisation and der Universitaet Dortmund, Dortmund, Germany

  • Lerner ND, Kotwal BM, Loyns RD, Gardner-Bonneau DJ (1996) Preliminary human factors guidelines for crash avoidance warning devices (NHTSA DOT HS 808 342). COMSIS, Silver Spring

  • Michon JA (1985) A critical view of driver behaviour models: what do we know, what should we do. In: Evans L, Laoschwing RC (eds) Human behaviour and traffic safety. Plenum Press, New York, pp 485–520

  • Naatanen R, Summala H (1973) A model for the role of motivational factors in drivers' decision making. Accid Anal Prev 6:243–261

    Article  Google Scholar 

  • Nilsson L, Stevens A, Roskes A, Heinrich J (2001) Behavioural risk analysis. In: Bekiaris E, Papakonstantinou G (eds) D3/8.1 of ADVISORS project, Aristotle University of Thesaloniki, Laboratory of Transport Engineering, Thessaloniki, Greece

  • Périsse J, Baligand B, Bellotti F, Friedemann K, Amditis A, Montanari R, Morreale D (2001) Channel harmonisation. Deliverable 3.3 of COMUNICAR project, Metravib RDS, Limonest, France

  • Rasmussen J (1984) Information processing and human–machine interaction. An approach to cognitive engineering. North-Holland, New York

  • Rothengatter T (1997a) Errors and violations as factors in accident causation. In Rothengatter, Vaya (eds) Traffic and transport psychology. Pergamon, Amsterdam, pp 59–64

  • Rothengatter T (1997b) Psychological aspects of road user behaviour. Appl Psychol 46(3):132–151

    Article  Google Scholar 

  • Verwey WB, Brookhuis KA, Janssen WH (1996) Safety effects of in-vehicle information systems (Report TM-96-C002). TNO Human Factors Research Institute, Soesterberg, The Netherlands

  • Wilde GJS (1994) Risk homeostasis theory and its promise for improved safety. In: Trimpop RM, Wilde GJS (eds) Challenges to accident prevention: the issue of risk compensation behaviour. Styx Publications, Groningen, The Netherlands

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Bekiaris, E., Amditis, A. & Panou, M. DRIVABILITY: a new concept for modelling driving performance. Cogn Tech Work 5, 152–161 (2003). https://doi.org/10.1007/s10111-003-0119-x

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  • DOI: https://doi.org/10.1007/s10111-003-0119-x

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