Epsilon Archive for Student Projects

Abstract

Urban planning strategies have a fundamental impact on people’s choice of transport. Many European cities are working to shift towards facilitating more sustainable modes of transport and reducing motorised traffic.

Cognitive load can be considered the mental resources that are required to perform a variety of tasks, such as cycling in various traffic situations. Human factors, i.e., cognitive load, affect people's perceived safety and their choice of transport mode. There is a lack of naturalistic cycling data focusing on the influence of different traffic conditions on cognitive load.

Therefore, this study aims to investigate the influence of different traffic situations on the cognitive load of cyclists. For that, people participate in a naturalistic study, cycling through the Austrian city of Vienna, in order to advance research regarding the effects of various built environment conditions and traffic volume on cognitive load. The effects of the different conditions are compared. Cognitive load can be assessed by physiological measurements (i.e., through Empatica E4 smartwatch) in the form of electrodermal activity (EDA). For this study, EDA has been normalised compared to people’s baseline physiological responses.

A panel regression model is used to investigate the effect of different built environment conditions and traffic volume on cyclists’ cognitive load. The results confirm differences between the various traffic segments on cognitive load but are not in line with the hypothesis that higher traffic volume leads to increased cognitive load. Although not all results confirm the hypotheses, this study shows that cognitive load, measured through EDA can improve understanding of the effect of different built environment conditions on cyclists’ cognitive load in a dynamic traffic context.