A typological and spatial analysis of pedestrian fatalities and injuries in Malta

Abstract

Car oriented urban areas are characterised by pedestrian-vehicle collisions. The aim of this paper is to examine such collisions between 2004 and 2018 and determine the characteristics of accident and injury risk for pedestrians in Malta. First, we investigated the relationship between the variables (age, gender, month, day, time, district, injury, and category) to establish the accident characteristics using a Multiple Correspondence Analysis (MCA). Second, we categorised the results from the MCA into groups by means of a Cluster Analysis. Third, we analysed spatially the categories by means of Kernel Density Estimation (KDE). The typological analysis provided two dimensions of pedestrian injuries namely, month and vehicle category, and age and time; these were the characteristics that were over-represented in comparison to the whole dataset of pedestrian injuries. The outputs of the Cluster Analysis provided clusters of types of injured pedestrians that are worth looking for planning and policy making, such as Group 2 the Summer party people. The KDE revealed patterns that should be investigated in future research on the relationship between pedestrian-vehicle collisions and the built environment. These findings are useful to urban planners and transport engineers to design policies and measures aimed at improving pedestrian road safety.