Multidimensional evaluation of public transport accessibility

Abstract

Public transport conditions are analysed using simulated commuting to important employers and recording data about significant features of all simulated trips. Two forms of overall public transport accessibility evaluation are compared— rule based and multivariate based classifications. Rule based classification was developed in several variants integrating two or four indicators, average and non-aggregated values. More valuable results were obtained using extended set of indicators for non-aggregated trips. The multivariate classification utilizes a novel approach to K-means cluster analysis using decile values. The comparison of both classifications shows a primary role of expert based classification. K-means cluster analysis based on deciles or median values are suitable for establishing more common typology but not for a local accessibility evaluation.