Understanding the Impacts of Connected Autonomous Vehicles on Pedestrians with Visual Impairment

Abstract

This thesis develops a policy-framework that can be used for minimizing communication issues between connected autonomous vehicles (CAVs) and visually impaired pedestrians. The existing literature on CAVs is highly focused on different perspectives of the possible users of these technologies. Since, this research uses a dataset collected through a tailor-made stated adaptation survey among visually impaired pedestrians. The dataset includes the current mobility issues of this community, their perceptions about CAVs, and a wide range of socioeconomic attributes. Some evidence-based recommendations are provided on communication techniques, based on the key findings of a series of structural equation models (SEM) and ordered logit models estimated using the survey data. The results reveal that the low-noise issue of electric engines influences visually impaired pedestrians’ safety and security in the contexts of CAVs. It shows that respondents who rely on mobile applications and technology-based devices for navigating purposes tend to trust in CAVs.