Using Multiple Correspondence Analysis for large driving signals database exploration. Example with lane narrowing and curves
P Loslever, JC Popieul, P Simon… - 2010 IEEE intelligent …, 2010 - ieeexplore.ieee.org
P Loslever, JC Popieul, P Simon, A Todoskoff
2010 IEEE intelligent vehicles symposium, 2010•ieeexplore.ieee.orgIn most driving studies, several factors (at least two, ie individual and time) and many
variables are collected via multidimensional signals (MS). This article suggests starting the
analysis while keeping the three main aspects of time, ie simultaneity, chronology and
duration. To achieve this aim, with the possibility to show nonlinear relationships, a MS set
exploratory investigation is performed using the pair space-time windowing/Multiple
Correspondence Analysis. This article shows how intra and inter-individual differences can …
variables are collected via multidimensional signals (MS). This article suggests starting the
analysis while keeping the three main aspects of time, ie simultaneity, chronology and
duration. To achieve this aim, with the possibility to show nonlinear relationships, a MS set
exploratory investigation is performed using the pair space-time windowing/Multiple
Correspondence Analysis. This article shows how intra and inter-individual differences can …
In most driving studies, several factors (at least two, i.e. individual and time) and many variables are collected via multidimensional signals (MS). This article suggests starting the analysis while keeping the three main aspects of time, i.e. simultaneity, chronology and duration. To achieve this aim, with the possibility to show nonlinear relationships, a MS set exploratory investigation is performed using the pair space-time windowing/Multiple Correspondence Analysis. This article shows how intra and inter-individual differences can be underscored.
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