Some results obtained in the framework of a research project that has the main objective of developing a methodology to analyse the combined effect of multiple stressors acting simultaneously on passengers riding in vehicles were presented. It was possible to evaluate physical quantities characterising the environmental conditions in a bus passenger compartment in terms of comfort, and derive some of the evaluation indices commonly used for each kind of stimulus. Beside the physical measurements, subjective assessment of the discomfort sensation felt by panels of evaluators was also collected through the use of a questionnaire. An artificial neural network (ANN) has been used to correlate data about votes on a general comfort scale with the votes about different stimuli. The same technique will be used in the near future to correlate subjective votes with comfort indices derived from physical measurements. The results presented show that ANN can represent a sound improvement in the methodologies to evaluate the comfort in vehicles. The intention is to develop the modelling capabilities further for the prediction of global comfort using as inputs the objective measured parameters for each stimulus considered, thus giving vehicle manufacturers a tool to evaluate the performance of their models and to improve vehicle friendliness to passengers. Further tests are needed to have an amount of information that warrants a good covering of different environmental conditions that usually occur in passengers compartments, in order to assure that ANN has been trained sufficiently.


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    Titel :

    Indoor environment in vehicles


    Weitere Titelangaben:

    Internes Umfeld in Fahrzeugen


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2006


    Format / Umfang :

    14 Seiten, 9 Bilder, 1 Tabelle, 14 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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