The ISi-PADAS Project—Human Modelling and Simulation to support Human Error Risk Analysis of Partially Autonomous Driver Assistance Systems
The objective of this paper is to discuss the goals and scope of the EU project ISi-PADAS, its theoretical backgrounds and assumptions and the principal results achieved to date. Models of driver behaviour and of Joint Driver- Vehicle-Environments (JDVE) systems, as well as “classical” reliability analysis methods, represent the starting points of the proposed research plan.
The main aim of this Project is to support the design and safety assessment of new generations of assistance systems. In particular, the development of autonomous actions is proposed, based on driver models able to predict performances and reaction time, so as to anticipate potential incidental conditions. To achieve this objective two main integrated lines of development are proposed: (1) an improved risk based design approach, able to account for a variety of human inadequate performances at different levels of cognition, and (2) the development of a set of models for predicting correct and inadequate behaviour.
This paper shows that different kinds of JDVE models and evolutionary risk analysis approaches are required to achieve the goals of the Project. Possible solutions are presented and discussed. In addition, a methodological framework is introduced that is capable to accommodate different types of models and methods while maintaining the same safety and risk assessment objectives.
KeywordsDriver modelling Driver Assistance Systems Risk Based Design Human Reliability Assessment Cognitive modelling
The authors would like to thank all the Partners of ISi-PADAS for their motivated and continuous work of research, carried out patiently and with enthusiasm by everyone in the first two years of collaboration. Without this support we would not have been able to report and discuss about such a remarkable achievement made so far by the ISi-PADAS team.
- 1.Aasman J (1995) Modelling driver behaviour in soar. KPN Research, LeidschendamGoogle Scholar
- 2.Bellet T, Bailly B, Mayenobe P, Georgeon O (2007) Cognitive modelling and computational simulation of drivers mental activities. In: Cacciabue PC, Re C (eds) Critical Issues in advanced automotive systems and human-centred design. Springer Verlag, London, pp 317–345Google Scholar
- 3.Briest S, Vollrath M (2006) In welchen situationen machen fahrer welche fehler? Ableitung von anforderungen an fahrerassistenzsysteme durch in-depth-unfallanalysen. In VDI (ed.) Integrierte sicherheit und fahrerassistenzsysteme. VDI, Wolfsburg, pp 449–463Google Scholar
- 4.Cacciabue PC (ed) (2007) Modelling driver behaviour in automotive environments: critical issues in driver interactions with intelligent transport systems. Springer-Verlag, LondonGoogle Scholar
- 6.Evans L (1985) Human behaviour feedback and traffic safety. Hum Factors 27(5):555–576Google Scholar
- 7.Forbes J, Huang T, Kanazawa K, Russell S (1995) The BATmobile: towards a bayesian automated taxi. In: Proceedings of international joint conference on artificial intelligence, vol 2. Morgan Kaufmann Publishers Inc, San Francisco, CA, USA, pp 1878–1885Google Scholar
- 9.IEC (2003). Functional safety-safety instrumented systems for the process industry sector. IEC 61511—International Electrotechnical Commission.Google Scholar
- 10.Kumagai T, Akamatsu, M (2006) Prediction of Human Driving Behavior Using Dynamic Bayesian Networks. IEICE-Transactions on Info and Systems, E89-D, (2): 857–860Google Scholar
- 11.Leonardi L, Mamei M, Zambonelli F (2004) Co-Fields: towards a unifying model for swarm intelligence. In: Engineering societies in the agents world III: third international workshop, vol 2577, Lecture Notes in Artificial Intelligence. Springer-Verlag, pp 68–81Google Scholar
- 12.Lüdtke A, Möbus C (2005) A case study for using a cognitive model of learned carelessness in cognitive engineering. In Salvendy G (ed) Proceedings of the 11th international conference on human-computer interaction (HCI international’05). Lawrence Erlbaum Associates, Inc, MahwahGoogle Scholar
- 13.McRuer DT, Allen RW, Weir DH, Klein RH (1977) New results in driver steering control. Hum Fact 19:381–397Google Scholar
- 14.Michon JA (1985) A critical review of driver behaviour models: What do we know? What should we do? In: Evans LA, Schwing RC (eds) Human behaviour and traffic safety. Plenum Press, New York, pp 487–525Google Scholar
- 15.Muhrer E, Vollrath M (2009) Re-analysis of in-depth accident studies to generate hypotheses about causes of driver errors. Deliverable 1.1 of the ISi-PADAS project, pp 12–16.Google Scholar
- 18.Swain AD, Guttmann HE (1983) Handbook on human reliability analysis with emphasis on nuclear power plant application. NUREG/CR-1278. SAND 80-0200 RX, AN. Final Report.Google Scholar
- 19.Vaa T (2001) Cognition and emotion in driver behaviour models: Some critical viewpoints. In: Proceedings of the 14th ICTCT workshop, Caserta.Google Scholar
- 20.Zhang Y, Owechko Y, Zhang J (2004) Learning-based driver workload estimation. In: Proceedings of 7th international symposium on advanced vehicle control, Arnhem.Google Scholar