Cycling in the Age of Automation: Enhancing Cyclist Interaction with Automated Vehicles through Human-Machine Interfaces

This dissertation explores cyclist-automated vehicle interactions, emphasising developing and integrating human-machine interfaces (HMIs) to enhance cyclist safety and communication. Adopting a cyclist-centric perspective, it recognises cyclists' unique characteristics and communication strategies in shared traffic environments. Using semi-structured interviews, literature reviews, data triangulation, an eye-tracking field experiment, and a cycling simulator study, the research addresses five key research questions, providing qualitative and quantitative insights.

The main contributions of this dissertation include a thorough investigation of cyclists' expectations for future interactions with automated vehicles, highlighting the need for reliable detection by automated vehicles and placing the responsibility for safety on vehicle developers rather than cyclists. The research offers objective data and self-reported insights into cyclist-automated vehicle interactions and evaluates cyclists' ability to visually detect the presence or absence of a driver. Additionally, it introduces 20 scenarios of cyclist-automated vehicle interaction, serving as a resource for safety assessments and HMI research. A comprehensive literature review of existing HMIs for cyclists was conducted, identifying 92 concepts involving vehicles, bicycles, cyclists, and infrastructure.

The dissertation concludes with design recommendations for cyclist-centric HMIs, proposing an omnidirectional on-vehicle external HMI (eHMI) to communicate detection and automated driving mode. This dissertation provides valuable insights for researchers, policymakers, and automated vehicle developers, aiming for the safer, more inclusive, and sustainable urban traffic environments of tomorrow.