Analysis of walking patterns in a pedestrian environment using cellular automata

Abstract

Pedestrian urban spaces are conducive to the critical economic, environmental and social challenges pertaining to the use of predominantly motorised transport systems. Pedestrian environments (PEs) create spaces that ameliorate social attitude and safety in addition to the movement of people. Designing PEs in accordance with the pattern of pedestrian movement has the potential to more fully realise their benefits, hence the importance of studying pedestrian behaviour. In order to do so, a newly established PE located in Qazvin, Iran, was chosen. The study is based on the data collected from traffic cameras during peak hours. Through the use of a cellular automata and discrete choice models, the data were employed so as to analyse factors such as speed, gender, pedestrian position, movement direction and the presence of other pedestrians and obstacles, and their effects on the pattern of pedestrian movement. Based on the findings, the male adult pedestrians with higher walking speeds preferred to move with long steps in the middle of the PE away from the commercial areas, while the female adult pedestrians preferred to move alongside the areas adjacent to the commercial areas.