An Inclusive Design Approach to Integrating an External Human Machine Interface with Autonomous Vehicles

As autonomous vehicles become more prevalent in urban traffic settings, the safety of vulnerable road users, predominantly pedestrians, must be placed in high regard relative to the design of the autonomous vehicle\u27s (AV\u27s) external human machine interface (HMI). Traditionally, there exist communication methods between drivers and pedestrians, such as hand gestures, eye contact, and verbal cues that convey the driver\u27s awareness of the pedestrian\u27s presence. However, with autonomous vehicles, there is a shift in communicative responsibility from the driver to the vehicle itself. It is the vehicle\u27s responsibility to intuitively and clearly indicate its actions to the pedestrian. This research analyzes the factors contributing to AV skepticism and the ways in which the visual aspect of an AV\u27s external HMI can be improved from traditional vehicle designs to accommodate visually impaired pedestrians. This was achieved by performing a study on 27 participants varying in age, gender, and vision impairment type. The study includes a survey and interview portion. Findings indicate that yellow and blue colors are viewed as most welcoming and memorable. It is suggested that these colors be used in the projected light system of the external HMI design. Quantitative results indicate that there is a moderate degree of correlation between the following: the use of cruise control and vision impairment severity (negative correlation), a participant\u27s willingness to ride in an AV and vision impairment levels (positive correlation). The study also found a low degree of correlation in a participants willingness to ride in an AV and their trust in AVs. Based on these findings and under the assumption than an external HMI is needed on the AV, it is recommended that the external HMI contain a light projection system on the vehicle\u27s front body. Based on qualitative results, the light projection system should use a teal color light and project a directional arrow onto the ground when identifying a pedestrian in its path while turning. Intuitive signals such as these help ensure pedestrian safety and promote trust and acceptance of the use of autonomous vehicles on public roads

Ehmi: Review and guidelines for deployment on autonomous vehicles

Human-machine interaction is an active area of research due to the rapid development of autonomous systems and the need for communication. This review provides further insight into the specific issue of the information flow between pedestrians and automated vehicles by evaluating recent advances in external human-machine interfaces (eHMI), which enable the transmission of state and intent information from the vehicle to the rest of the traffic participants. Recent developments will be explored and studies analyzing their effectiveness based on pedestrian feedback data will be presented and contextualized. As a result, we aim to draw a broad perspective on the current status and recent techniques for eHMI and some guidelines that will encourage future research and development of these systems

Accessible Automated Automotive Workshop Series (A3WS): International Perspective on Inclusive External Human-Machine Interfaces

The fact that automated vehicles will be part of road traffic raises the question of how human road users, like bicyclists or pedestrians, would safely interact with them. Research has proposed external human-machine interfaces (eHMIs) for automated vehicles as a potential solution. Concept prototypes and evaluations so far have mainly focused on young, healthy adults and people without disabilities, such as visual impairments. For a “one-for-all” holistic, inclusive solution, however, further target groups like children, seniors, or people with (other) special needs will have to be considered. In this workshop, we bring together researchers, experts, and practitioners working on eHMIs to broaden our perspective on inclusiveness. We aim to identify aspects of inclusive eHMI design that can be universal and tailored to any culture and will focus on discussing methods, tools, and scenarios for inclusive communication

Accessible Autonomy: Exploring Inclusive Autonomous Vehicle Design and Interaction for People who are Blind and Visually Impaired

Autonomous vehicles are poised to revolutionize independent travel for millions of people experiencing transportation-limiting visual impairments worldwide. However, the current trajectory of automotive technology is rife with roadblocks to accessible interaction and inclusion for this demographic. Inaccessible (visually dependent) interfaces and lack of information access throughout the trip are surmountable, yet nevertheless critical barriers to this potentially lifechanging technology. To address these challenges, the programmatic dissertation research presented here includes ten studies, three published papers, and three submitted papers in high impact outlets that together address accessibility across the complete trip of transportation. The first paper began with a thorough review of the fully autonomous vehicle (FAV) and blind and visually impaired (BVI) literature, as well as the underlying policy landscape. Results guided prejourney ridesharing needs among BVI users, which were addressed in paper two via a survey with (n=90) transit service drivers, interviews with (n=12) BVI users, and prototype design evaluations with (n=6) users, all contributing to the Autonomous Vehicle Assistant: an award-winning and accessible ridesharing app. A subsequent study with (n=12) users, presented in paper three, focused on prejourney mapping to provide critical information access in future FAVs. Accessible in-vehicle interactions were explored in the fourth paper through a survey with (n=187) BVI users. Results prioritized nonvisual information about the trip and indicated the importance of situational awareness. This effort informed the design and evaluation of an ultrasonic haptic HMI intended to promote situational awareness with (n=14) participants (paper five), leading to a novel gestural-audio interface with (n=23) users (paper six). Strong support from users across these studies suggested positive outcomes in pursuit of actionable situational awareness and control. Cumulative results from this dissertation research program represent, to our knowledge, the single most comprehensive approach to FAV BVI accessibility to date. By considering both pre-journey and in-vehicle accessibility, results pave the way for autonomous driving experiences that enable meaningful interaction for BVI users across the complete trip of transportation. This new mode of accessible travel is predicted to transform independent travel for millions of people with visual impairment, leading to increased independence, mobility, and quality of life

Principles for External Human-Machine Interfaces

Automated vehicles will soon be integrated into our current traffic system. This development will lead to a novel mixed-traffic environment where connected and automated vehicles (CAVs) will have to interact with other road users (ORU). To enable this interaction, external human–machine interfaces (eHMIs) have been shown to have major benefits regarding the trust and acceptance of CAVs in multiple studies. However, a harmonization of eHMI signals seems to be necessary since the developed signals are extremely varied and sometimes even contradict each other. Therefore, the present paper proposes guidelines for designing eHMI signals, taking into account important factors such as how and in which situations a CAV needs to communicate with ORU. The authors propose 17 heuristics, the so-called eHMI-principles, as requirements for the safe and efficient use of eHMIs in a systematic and application-oriented manner

The Application of Geographic Information Systems to Support Wayfinding for People with Visual Impairments or Blindness

People with visual impairments or legal blindness are relying on differing, comprehensive information utilized for their individual mobility. Increasing the personal mobility of people with disabilities and thereby achieving a self-determined life are major steps toward a more inclusive society. Research and applications on mobility issues of people with visual impairments or blindness mainly focus on technical applications or assistive orientation and navigation devices, and less work is covering the individual needs, e.g., regarding the information required for wayfinding. Moreover, active participation of people with disabilities in research and development is still limited. ways2see offers a new online application to support individual mobility in context of pre-trip planning for people with visual impairments or blindness based on a Geographic Information System (GIS). Obstacles, barriers, landmarks, orientation hints, and directions for wayfinding are generated by user profiles. The underlying network for GIS analysis is designed as pedestrian network. This individually coded network approach integrates sidewalks and different types of crossings and implements various orientation and navigation attributes. ways2see integrates three research realms: firstly, implementing a participative and transdisciplinary research design; secondly, integrating personalized information aligned with the individual user needs; and thirdly, presenting result of GIS analysis through an accessible designed user interface