As cycling becomes more popular and automated driving is on the rise, it can be assumed that in the city of the future highly automated vehicles (HA Vs) and cyclists will share the same roads. Yet only little is known about how cyclists announce their maneuvers to motorized vehicles or how they communicate and interact with them. Knowledge on these aspects is currently missing to guide the design of cyclist-HA V interactions. Situations where a cyclist rides upfront a vehicle, will be especially challenging for HA Vs, such as when a cyclist (A) avoids an obstacle on the road section ahead, (B) merges onto the road from an ending cycling path, or (C) leaves the road turning into a driveway {see Figure 1) [1 ]. Based on the cyclist's intention, the HA V will have to pass or keep following with only limited options to communicate to the cyclist ahead. Design solutions derived from the well-studied field of pedestrian-HA V interactions cannot simply be transferred to the here considered cyclist-HA V interactions, since in past research successful design concepts for pedestrians were not beneficial for cyclists [2]. Hence, it is vital to investigate the behavior and experiences of cyclists in more detail and to explore possible design solutions for HA V interaction behavior in these situations. With this study we aim to get more insights into the subjective experience of cyclists travelling in longitudinal traffic, especially during cyclist-vehicle interactions, as well as to derive cyclists' requirements to design safe and desirable cyclist-HA V interactions.

Automated vehicles (AVs) will be integrated into our society at some point in the future, but when is still up for debate. An extensive amount of research is being completed to understand the communication methods between AVs and other road users sharing the environment to prepare for this future. Currently, researchers are working to understand how different forms of external communication on the AVs will impact vulnerable road user (VRU) interaction. However, within the last 10 years, VRU casualty rates have continued to rise for all classifications of VRUs. Unfortunately, there is no suggestion that pedestrian fatality rates will ever decrease without some intervention. This dissertation aims at understanding the impacts of eHMI across real-world, complex scenarios with AVs and how researchers can apply those future findings to improve VRUs' judgments to today. A series of studies evaluated the necessity and impact of eHMI on AV–VRU interaction, assessed how the visual components of eHMI influenced VRU crossing decisions, and how variations in a real-world environment (multiple vehicles and scenario complexity) impact crossing decision behavior. Two studies examined how eHMI will impact future interactions between AVs and VRUs. Specifically, to understand how to advance the design of these future devices to avoid unintended consequences that may result. Results from these studies found that the presence and condition of eHMI did not influence participants' willingness to cross. Participants primarily relied on the speed and distance of the vehicle to make their crossing decision. It was difficult for participants to focus on the eHMI when multiple vehicles competed for their attention. Participants typically prioritized their focus on the vehicle that was nearest and most detrimental to their crossing path. Additionally, the type of scenario caused participants to make more cautious crossing decisions. However, it did not influence their willingness to cross. The last study applied the learnings from the first two studies to a foundational perception study for current legacy vehicles. These results showed a significant increase in judgment accuracies with a display. Through analysis across overall conclusions from the 3 studies, five critical findings were identified when addressing eHMI and 3 design recommendations, which are discussed in the penultimate section of this work. The results of this dissertation indicate that eHMI improved VRUs' accuracy of perception of change in vehicle speed. eHMI did not significantly impact VRUs crossing decisions. However, the complexity of the traffic scenarios affected the level of caution participants exhibited in their crossing behavior. / Doctor of Philosophy / An extensive amount of research is being completed to understand the communication methods between AVs and other road users sharing the environment to prepare for this future. Currently, researchers are working to understand how different forms of external communication on the AVs will impact vulnerable road user (VRU) interaction. However, within the last 10 years, VRU casualty rates have continued to rise for all classifications of VRUs. Unfortunately, there is no suggestion that pedestrian fatality rates will ever decrease without some intervention. This dissertation aims at understanding the impacts of eHMI across real-world, complex scenarios with AVs and how researchers can apply those future findings to improve VRUs' judgments to today. A series of studies evaluated the necessity and impact of eHMI on AV–VRU interaction, assessed how the visual components of eHMI influenced VRU crossing decisions, and how variations in a real-world environment (multiple vehicles and scenario complexity) impact crossing decision behavior.