Effective communication between automated vehicles (AVs) and human road users (HRU) in mixed traffic is essential for ensuring safety, trust and acceptance. However, existing research on external Human-Machine Interfaces (eHMI) for AVs often overlooks design factors and their interconnections, leading to suboptimal designs. This article presents a comprehensive framework of Human-Machine Interaction in mixed traffic, integrating different relevant stakeholders, influencing factors, and relationships. By visualizing the interactions during communication and with the surrounding environment, the framework serves as a valuable tool for research and development of eHMI, maintaining a comprehensive perspective. Key challenges include determining optimal design features, such as message transmission methods and integration into the vehicle exterior design, and considering diverse human factors, such as age, culture, and cognitive abilities. By addressing these challenges, future eHMI designs can enhance user acceptance and trust in AVs, contributing to safer and more efficient mixed traffic environments. Further research will delve into the detailed examination of design factors and the interaction between interior and exterior vehicle interfaces.

If automated vehicles are to be introduced on public roads, they need to be able to communicate appropriately with other road users. This can be done using various interfaces and by communicating various messages. Previous research has mainly investigated design of such communication for automated passenger cars. It is, however, currently largely unknown how corresponding communi- cation should be designed for heavy automated vehicles. Scania and RISE are collaborating in a research project on what signals need to be displayed for heavy automated vehicles when they get introduced to public roads. This thesis focuses on design of an external human-machine interface (eHMI) that conveys that a truck is operated in automated driving mode. It explored various types of message contents (abstract lights, text, symbols) as well as the effect of placement of eHMI (grille, under windshield, above windshield) and distance on understanding of the message. The emphasis was on the communi- cation to pedestrians in a crossing scenario. The thesis work was split into three design iterations according to the ”De- sign Thinking” methodology. The first iteration investigated the most preferred content types. The second investigated the effect that the screen placement on the truck had on the comprehensibility of the sign with regards to distance. The third and last iteration meant creating physical prototypes of low fidelity corresponding to the concepts from the second iteration, installing them on a truck and then evaluating them on a test track. The final evaluation was of an exploitative character and involved experts in the field of HMI design. The results showed that it was hard to interpret signals based on colors and abstract lights only. Symbols were also hard to interpret and should only be used when there is a standard for symbols for automated vehicles. Using text, on the other hand, made the message more clear and was easier to understand independently of the distance. As for the placement of the eHMI, the results show that there are preferences to using the middle and upper part of the truck.

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.

The study aimed to identify and analyse methods for establishing external communication between humans and autonomous/teleoperated machines/vehicles using various Human-Machine Interfaces (HMIs). The study was divided into three phases. The purpose of the first phase was to identify and highlight previously tested/researched methods for establishing external communication by conducting a literature review. The findings from the literature review were categorised into six points of interest: machine indications, test delivery methods, HMI technologies/types, symbols, textual/numerical messages, and colours associated with different indications. Based on these findings, four HMIs (projection, display, LED-strip, and auditory) were selected for evaluation in a virtual reality environment for the second phase of the study, which has the purpose of identifying which of the human-machine interfaces can effectively communicate the intentions of autonomous/teleoperated machines to humans. The results of phase two indicate that the participants preferred projection as the most effective individual HMI, and when given the option to combine two HMIs, projection combined with auditory was the most preferred combination. The participants were also asked to pick three HMIs of their choosing, resulting in the projection, display and audible HMI combination being the preferred option. The evaluation of HMIs in a virtual reality environment contributes to improving dependability and identifying usability issues.  The objective of the third and final phase was to gather all the findings from the previous phases and subsequently refine the report until it was considered finalised. Future work includes enhancing the realism of the VR environment, refining machine behaviour and scenarios, enabling multiple participants to simultaneously interact with the environment, and exploring alternative evaluation methods. Addressing these areas will lead to more realistic evaluations and advancements in human-machine interaction research.