Bridging Worlds: Augmented Reality for Pedestrian-Automated Vehicle Interactions

This thesis explores how automated vehicles will interact with pedestrians in the urban environment through augmented reality technology. Nine distinct AR interfaces were designed, developed, and evaluated to assess how different design elements (symbols, text, colour) and distinct mappings of the AR (on the road, on the vehicle, or head-locked) would affect comprehension, and ultimately whether the pedestrian would trust and be convinced to cross in front of an automated vehicle displaying a safe message. Using increasing levels of ecological validity, from an online questionnaire to a CAVE simulator and an AR HMD experiment, the evaluation also explored how different AR anchoring (and mapping) positions affect pedestrians' crossing initiation times and the intuitiveness of the message. The thesis also explores the use of diminished reality (removal of information) to assist pedestrians in occluded scenarios, as well as the utilisation of Large Language Models in evaluating qualitative data in experiments. The outcomes of the thesis are a set of guidelines based on empirical evidence on how to design effective AR interfaces which promote safe and transparent interactions between pedestrians and automated vehicles.