Multiple Correspondence Analysis (MCA) is a statistical technique used to present the relative closeness of the categorical variables from any dataset by analyzing data in the form of numerical frequencies and represent them graphically. Since pedestrian accidents data can be represented as transactions of multiple categorical variables, MCA can be a considered a good methodology to analyze the relationship among such variables. This paper is the study of application of MCA to analyze safety in the interaction among urban road transit and pedestrians. MCA is applied to a Bus Rapid Transit (BRT) line in the city of Catania, operating since 2013; during those years there were no accidents, but a series of traffic conflicts have happened; that’s the reason why authors proceed with the application of the methodology taking into account the occurrence of the so called “near misses”.

Using multiple correspondence analysis to improve safety in interaction between road transit and public spaces

Giuffrida, N.
Primo
;
Ignaccolo, M.;Inturri, G.
Ultimo
2018-01-01

Abstract

Multiple Correspondence Analysis (MCA) is a statistical technique used to present the relative closeness of the categorical variables from any dataset by analyzing data in the form of numerical frequencies and represent them graphically. Since pedestrian accidents data can be represented as transactions of multiple categorical variables, MCA can be a considered a good methodology to analyze the relationship among such variables. This paper is the study of application of MCA to analyze safety in the interaction among urban road transit and pedestrians. MCA is applied to a Bus Rapid Transit (BRT) line in the city of Catania, operating since 2013; during those years there were no accidents, but a series of traffic conflicts have happened; that’s the reason why authors proceed with the application of the methodology taking into account the occurrence of the so called “near misses”.
2018
9781351173360
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/366105
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