Skip to main content
SpringerLink
Log in

Context-sensitive decision support systems in road safety

  • Original Article
  • Published:
Information Systems and e-Business Management Aims and scope Submit manuscript

Abstract

Enterprises often embed decision-making processes in procedures in order to address issues in all cases. However, procedures often lead to sub-optimal solutions for any specific decision. As a consequence, each actor develops the practice of addressing decision making in a specific context. Actors contextualize decision making when enterprises are obliged to decontextualize decision making to limit the number of procedures and cover whole classes of decision-making processes by generalization. Practice modeling is not easy because there are as many practices as contexts of occurrence. This chapter proposes a way to deal effectively with practices. Based on a conceptual framework for dealing with context, we present a context-based representation formalism for modeling decision making and its realization by actors. This formalism is called contextual graphs and is discussed using the example of modeling car drivers’ behaviors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Bellet T, Tattegrain-Veste H, Bonnard A (2005) Risk of collision and behavior adequacy assessment for managing human-machine interaction. In: 11th international conference on human-computer interaction (HCI), Nevada, July

  • Brézillon P (1994) Context needs in cooperative building of explanations. In: First European conference on cognitive science in industry, Luxembourg, pp 443–450

  • Brézillon P (2005) Task-realization models in contextual graphs. In: Dey A, Kokinov B, Leake D, Turner R (eds) Modeling and using context (CONTEXT-05). LNCS, vol 3554. Springer, Heidelberg, pp 55–68

  • Brézillon P, Gonzalez JA (2006) Tale of two context-based formalisms for representing human knowledge. In: Ali M, Dapoigny R (eds) IEA/AIE 2006. LNAI, vol 4031. Springer, Heidelberg, pp 137–145

  • Brézillon P, Pomerol J-Ch (1997) User acceptance of interactive systems: lessons from knowledge-based and decision support systems. Failures and lessons learned. Inform Technol Manage 1(1):67–75

    Google Scholar 

  • Brézillon P, Pomerol J-Ch (1999) Contextual knowledge sharing and cooperation in intelligent assistant systems. Trav Hum 62(3):223–246

    Google Scholar 

  • Brézillon P, Cavalcanti M, Naveiro R, Pomerol J-Ch (2000) SART: an intelligent assistant for subway control. Pesquisa Operacional. Braz Oper Res Soc 20(2):247–268

    Google Scholar 

  • Brézillon P, Pomerol J-Ch, Pasquier L (2003) Learning and explanation in a context-based representation: application to incident solving on subway lines. In: Jain R, Abraham A, Faucher C, van der Zwaag J (eds) Innovations in knowledge engineering, chap 6. International Series on Advanced Intelligence, pp 129–149

  • Brézillon P, Brézillon J, Pomerol J-Ch (2006) Decision making at a crossroad: a negotiation of contexts. In: Proceedings of the joint international conference on computing and decision making in civil and building engineering, ISBN 2-921145-58-8, pp 2574–2583

  • Campbell B, Goodman J (1988) HAM: a general purpose hypertext abstract machine. Commun ACM 31(7):856–861

    Article  Google Scholar 

  • Clancey WJ (1992) Model construction operators. Artif Int J 53:1–115

    Article  Google Scholar 

  • Compton P, Jansen B (1988) Knowledge in context. A strategy for expert system maintenance. In: Siekmann J (ed) Lecture notes in artificial intelligence. Springer, Heidelberg, pp 37–49

    Google Scholar 

  • Forslund G (1995) Toward cooperative advice-giving systems. The expert systems experience. Ph.D. Dissertation, Linkoping University, Sweden

  • GADGET, An EU-project (1999) Guarding automobile drivers through guidance, education and technology. In: Siegrist S (ed) WP 3 report. BFU, Switzerland

  • Gonzales AJ, Ahlers RH (1998) Context-based representation of intelligent behaviour in training simulations. T Soc Comput Simul 15(4):153–166

    Google Scholar 

  • Grimshaw DJ, Mott PL, Roberts SA (1997) The role of context in decision making: some implications for database design. Eur J Inform Syst 6(2):122–128

    Article  Google Scholar 

  • Gruber T (1991) Justification-based knowledge acquisition. In: Motoda H, Mizoguchi R, Boose J, Gaines B (eds) Knowledge. Acquisition for Knowledge-based systems. IOS, Amsterdam, pp 81–97

    Google Scholar 

  • Hendrix G (1975) Expanding the utility of semantic networks through partitioning. In: Proceedings of the fourth IJCAI, pp 115–121

  • Henninger S (1992) The knowledge acquisition trap. In: Proceedings of the IEEE workshop on applying artificial intelligence to software problems: assessing promises and pitfalls (CAIA-92), Monterey, March

  • Laird JE, Newell A, Rosenbloom PS (1987) SOAR: an architecture for general intelligence. Artif Int 33:1–64

    Article  Google Scholar 

  • Leplat J, Hoc JM (1983) Tâche et activité dans l’analyse psychologique des situations. Cah Psychol Cogn 3:49–63

    Google Scholar 

  • McCarthy J (1993) Notes on formalizing context. In: Proceedings of the 13th IJCAI, vol 1, pp 555–560

  • Pomerol J-Ch (1997) Artificial intelligence and human decision making. Eur J Oper Res 99:3–25

    Article  Google Scholar 

  • Pomerol J-Ch (2001) Scenario development and practical decision making under uncertainty. Decis Support Syst 31:197–204

    Article  Google Scholar 

  • Pomerol J-CH, Brézillon P, Pasquier L (2002) Operational knowledge representation for practical decision making. J Manage Inform Syst 18(4):101–116

    Google Scholar 

  • Schank RC (1982) Dynamic memory, a theory of learning in computers and people. Cambridge University Press, London

    Google Scholar 

  • Sowa JF (2000) Knowledge representation: logical, philosophical, and computational foundations. Brooks Cole, Pacific Grove

    Google Scholar 

  • Van Elsandre P (2001) Dynamique des connaissances, catégorisation et attentes dans une conduite humaine située. Ph.D. Dissertation, Université Paris V

  • Vergnaud G (1985) Concepts et schèmes dans la théorie opératoire de la représentation. Les Représentation. Psychol Française 30(3):245–252

    Google Scholar 

Download references

Acknowledgments

The work presented in this paper is part of the ACC project supported by PREDIT and the French Minister of Transportation, primarily through the funding of a Ph.D. thesis. We also want to thank the other members of the ACC project, especially T. Artières, P. Gallinari, and C. Tijus.

Author information

Authors and Affiliations

  1. LIP6, University Paris 6, Paris, France

    Patrick Brézillon & Juliette Brézillon

Authors
  1. Patrick Brézillon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juliette Brézillon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Patrick Brézillon.

Additional information

This article is part of the “Handbook on Decision Support Systems” edited by Frada Burstein and Clyde W. Holsapple (2008) Springer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brézillon, P., Brézillon, J. Context-sensitive decision support systems in road safety. Inf Syst E-Bus Manage 6, 279–293 (2008). https://doi.org/10.1007/s10257-008-0088-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10257-008-0088-y

Keywords

Search

Navigation