Designing and Evaluating External Human-Machine Interfaces for Pedestrians- Autonomous Vehicle Interaction

Date of Award


Degree Name

Doctor of Philosophy


Civil and Construction Engineering

First Advisor

Valerian Kwigizile, Ph.D.

Second Advisor

Jun-Seok Oh, Ph.D.

Third Advisor

Zachary D. Asher, Ph.D.


With the emergence of Autonomous Vehicles (AVs), the traditional communication cues between drivers and pedestrians have been disrupted, necessitating the development of external Human-Machine Interfaces (eHMIs) to fill this gap. Researchers and designers of AVs have been designing and evaluating many eHMIs concepts to allow AVs to effectively interact with other road users. The majority of these concepts were found to be beneficial for road users in simple one-to-one interaction scenarios. However, there is a lack of research on designing and evaluating eHMIs that can be effective in scenarios involving multiple road users. This research delves into the challenges and solutions associated with AV-to-pedestrian communication, combining findings from three studies.

The first study explored how pedestrians currently interact with regular cars and drivers, focusing on the signals they rely on to cross streets safely. Pedestrians' informational needs when interacting with AVs were also investigated. By surveying 317 pedestrians, the study reveals that pedestrians deeply value clear and direct communication methods, like hand gestures or eye contact, which are naturally missing from AVs, especially in locations where road markings are either unclear or missing. Moreover, it was found that the AV's movement intention and ability to cooperate are required in all traffic situations, while communication of the AV's perception of the surroundings and driving mode information are only important in scenarios involving multiple road users. Study findings highlight a pressing need for AVs to find new ways to clearly communicate with pedestrians.

The second study involved conducting two focus group discussions and drawing sessions to gather participants’ feedback about AV communication in mixed traffic situations and to come up with design ideas for eHMIs. In focus groups, eleven participants expressed mixed opinions about AVs, some of which were optimistic about their potential benefits, while others expressed skepticism about their accuracy and safety. All of the participants expressed a desire for clear communication from AVs, including information about the AV's mode, intention, surroundings detection, advising, and time to cross. The participants also discussed the criteria for designing effective eHMIs, emphasizing the importance of simplicity, clarity, visibility, and not directing messages to specific individuals. In drawing sessions, participants generated 31 designs, with symbol modality being the most common. Multiple modalities were used more frequently in the designs, with text and symbol being the most common combination.

The third study employed a mixed-methods approach including controlled experiments and intercept surveys. The aim of this study was to evaluate the impact of various eHMI displays on pedestrian behavior in mixed-traffic crossing scenarios. Findings revealed that the combination of a Flashing Green LED, Robotic Sign, and Countdown Timer constitutes the most effective eHMI display. This configuration not only increased the willingness to cross but also reduced the response time of pedestrians, indicating a clear understanding of the AV's intentions.

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