By Erik Hollnagel (auth.), P. Carlo Cacciabue, Magnus Hjälmdahl, Andreas Luedtke, Costanza Riccioli (eds.)
In glossy society, the individual is the significant component of the layout means of non-fully computerized keep watch over and defense process, in addition to the main resource and contributor to injuries. consequently, accounting for human modelling is critical in layout techniques and in defense exams, as a way to make sure applicable attention of human components. those matters are relatively actual for the area of transportation, the place safeguard similar elements are of paramount value for his or her effect on citizen health, in attention of the straightforward undeniable fact that nearly all people makes day-by-day utilization of private and non-private transportation platforms.
Even even though the behavioural and cognitive technological know-how has handled this challenge for many years, the problem of modelling human behaviour is still important to the subject of layout of human-machine structures. To take on this factor, 3 ecu Co-funded tasks, ISi-PADAS, ITERATE and HUMAN, will offer, in numerous domain names, total types of the joint cognitive platforms, represented through the human up to the mark, the ruled computing device and the operating setting. those types, as well as offering a stronger figuring out of the interactions among human and machines in a layout standpoint, let the honour of human mistakes in risk-based techniques and the advance of acceptable countermeasures.
The aim of this publication, that is the outcome the Workshop “Human Modelling in Assisted Transportation” (HMAT), is to supply an outline of the cutting-edge of the matter of human behaviour modelling in transportation platforms, and to confront types, tools and instruments built inside those 3 tasks with the continued examine conducted worldwide.
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Extra resources for Human Modelling in Assisted Transportation: Models, Tools and Risk Methods
Authority and Responsibility ‘Erroneous’ behaviours may be classified into two types: (1) omission-like behaviour failing to select or implement an action needed in a given situation and (2) commission-like behaviour to select and implement an action inappropriate to a given situation. The former corresponds to case A and the latter to case B in Fig. 1, respectively, under the assumption of technology to sense and interpret traffic conditions and driver behaviours, as well as the three-class categorization of the driver’s control action as (a) an action that needs to be done in the given situation, (b) an action that is allowable in the situation, and (c) an action that is inappropriate and thus must not be done in the situation.
Inagaki T (2010) Traffic systems as joint cognitive systems: issues to be solved for realizing human-technology coagency. Cogn Tech Work. 12(2):153–162 9. Inagaki T, Stahre J (2004) Human supervision and control in engineering and music: similarities, dissimilarities, and their implications. Proc IEEE 92(4):589–600 10. Inagaki T, Sheridan TB (2008) Authority and responsibility in human–machine systems: Is machine-initiated trading of authority permissible in the human-centered automation framework?
Vaa T (2011) Proposing a driver behaviour model based on emotions and feelings: exploring the limitations of perception and learning. In: Regan M, Trent V, Lee J (eds) Driver distraction and inattention: advances in research and countermeasures, vol 1, Ashgate, june 2011 (in press) 18. Wilde GJS (1982) The theory of risk homeostasis: implications for safety and health. Risk Anal 2:209–225 To What Extent May Assistance Systems Correct and Prevent ‘Erroneous’ Behaviour of the Driver? Toshiyuki Inagaki Abstract An error in situational recognition may occur while driving a car, and the error can sometimes result in an ‘erroneous’ behaviour of the driver.
Human Modelling in Assisted Transportation: Models, Tools and Risk Methods by Erik Hollnagel (auth.), P. Carlo Cacciabue, Magnus Hjälmdahl, Andreas Luedtke, Costanza Riccioli (eds.)