Peer Reviewed Journal Articles – VEMI Lab

Dude, Where’s My (Autonomous) Car? Defining an Accessible Description Logic for Blind and Low Vision Travelers Using Autonomous Vehicles

ederosby — Thu, 16 Oct 2025 18:13:33 +0000

Purpose: Autonomous vehicles (AVs) are becoming a promising transportation solution for blind and low-vision (BLV) travelers, offering the potential for greater independent mobility. This paper explores the information needs of BLV users across multiple steps of the transportation journey, including finding and navigating to, entering, and exiting vehicles independently.

Methods: A survey with 202 BLV respondents and interviews with 12 BLV individuals revealed the perspectives of BLV end-users and informed the sequencing of natural language information required for successful travel. Whereas the survey identified key information needs across the three trip segments, the interviews helped prioritize how that information should be presented in a sequence of accessible descriptions to travelers.

Results: Taken together, the survey and interviews reveal that BLV users prioritize knowing the vehicle’s make and model and how to find the correct vehicle during the navigation phase. They also emphasize the importance of confirmations about the vehicle’s destination and onboard safety features upon entering the vehicle. While exiting, BLV users value information about hazards and obstacles, as well as knowing which side of the vehicle to exit. Furthermore, results highlight that BLV travelers desire using their own smartphone devices when receiving information from AVs and prefer audiobased interaction.

Conclusion: The findings from this research contribute a structured framework for delivering trip-related information to BLV users, useful for designers incorporating natural language descriptions tailored to each travel segment. This work offers important contributions for sequencing transportation-related descriptions throughout the AV journey, ultimately enhancing the mobility and independence of BLV individuals.

Citation:

Fink, P.D.S., Brown, J.R., Coombs, R., Hamby, E.A., James, K.J., Harris, A., Bond, J., Andrulis, M.E., & Giudice, N.A. (in press). Dude, Where’s My (Autonomous) Car? Defining an Accessible Description Logic for Blind and Low Vision Travelers Using Autonomous Vehicles. Universal Access in the Information Society (UAIS).

Does Trust Even Matter? Behavioral Evidence for the Disconnect Between People’s Subjective Trust and Decisions to Use Autonomous Vehicles

ederosby — Wed, 21 May 2025 16:47:08 +0000

One of the most prevalent findings in the autonomous transportation literature is the strong connection between human trust and intentions to use autonomous vehicles (AVs). Indeed, trust is widely regarded as an essential antecedent for the adoption of AVs, a finding based primarily on survey-based methodologies. However, psychological theory has long suggested that self-reported measures of intention are fraught with contradiction – people often say one thing and do another. We examine this potential dichotomy here by experimentally characterizing the relationship between self-reported trust and behavioral decisions to use AVs. An initial survey of 444 participants assessed trust in AVs, identifying three trust categories: high, moderate, and low. Results demonstrated that people trust human rideshare drivers more than AVs. A subsequent in-lab behavioral study with 72 of these participants involved choosing a ride in an AV or a human-driven vehicle. Contrary to prevailing assumptions, our results reveal a deep chasm between intention and behavior: 97 % of participants, regardless of trust rating, chose to ride in the AV. This finding indicates that situational context, curiosity, and immediate circumstances heavily influence decision-making, mediating (and even overshadowing) self-reported trust levels. Employing Cognitive Dissonance Theory, we offer potential explanations for why participants reconciled their initial distrust with their subsequent actions. Our findings challenge the narrative that self-reported trust determines AV adoption and highlight the importance of situational factors in shaping user behavior. Using these results, we offer new insights and guidance for deploying AVs, suggesting that controlled, low-risk environments could facilitate broader acceptance of this emerging technology, providing a practical solution to the AV trust problem.

Citation:

Fink, P.D.S., Brown, J.R., Kutzer, K.M., & Giudice, N.A. (2025). Does Trust Even Matter? Behavioral Evidence for the Disconnect Between People’s Subjective Trust and Decisions to Use Autonomous Vehicles. Transportation Research Part F: Traffic Psychology and Behaviour (TRF), 114, 99-117. DOI: 10.1016/j.trf.2025.05.024.

Non-Visual Interfaces for Visual Learners: Multisensory Learning of Graphic Primitives

aforbes — Mon, 09 Dec 2024 18:40:05 +0000

Multimodal learning systems have been found to be effective in studies investigating cognitive theory of multimedia learning. Yet this research is rarely put into practice in Science, Technology, Engineering, and Math (STEM) learning environments, which are dominated by visual graphics. Introducing multimodal learning systems into STEM settings and allowing students to access dual channel cues beyond visual perception may help more students process information in their preferred modality. The purpose of this study was to investigate the usability, effectiveness, and design of multimodal interfaces for enhancing access to graphical representations. We used existing theories of multisensory information processing to study how sighted participants could learn and interpret spatial primitives and graphical concepts presented via three non-visual conditions: natural language (NL) descriptions, haptic renderings, and a NL-Haptic combination. The results showed that access to haptic-only renderings produced the least accurate responses, whereas NL descriptions with and without haptics led to similar performance by participants when learning graphical content without vision. Performance was also impacted by the complexity of the graphical content, with the highest level of accuracy observed for closed forms, compared to paired line segments and line/polygon intersections. We argue that universally designed, multimodal learning environments can transcend traditional, visual diagrams by utilizing non-visual channels and commercial hardware to support learners with different sensory abilities, preferences, and processing needs. Findings contribute to extending theoretical insights of non-visual information processing to better understand multisensory learning in sighted individuals.

Citation: Doore, Stacy A., Justin R. Brown, Saki Imai, Justin K. Dimmel, and Nicholas A. Giudice. “Non-Visual Interfaces for Visual Learners: Multisensory Learning of Graphic Primitives.” IEEE Access 12 (2024): 189926–40. .

Bridging the Gap of Graphical Information Accessibility in Education With Multimodal Touchscreens Among Students With Blindness and Low Vision

aforbes — Fri, 15 Nov 2024 17:16:33 +0000

Informational graphics and data representations (e.g., charts and figures) are
critical for accessing educational content. Novel technologies, such as the multimodal
touchscreen which displays audio, haptic, and visual information, are promising for being
platforms of diverse means to access digital content. This work evaluated educational graphics rendered on a touchscreen compared to the current standard for accessing graphical content.

Citation:
Tennison, J. L., Goswami, S., Hairston, J. R., Merlin Drews, P., Smith, D. W., Giudice, N. A., Stefik, A., & Gorlewicz, J. L. (2023). Bridging the Gap of Graphical Information Accessibility in Education With Multimodal Touchscreens Among Students With Blindness and Low Vision. Journal of Visual Impairment & Blindness, 117(6), 453-466. https://doi.org/10.1177/0145482X231217496

Download PDF

Give us something to chauffeur it: Exploring user needs in traditional and fully autonomous ridesharing for people who are blind or visually impaired

aforbes — Mon, 18 Sep 2023 16:21:15 +0000

As self-driving technology advances, there is enormous potential to optimize fully autonomous vehicles (FAVs) for use by people who are blind and visually impaired (BVI). Today, BVI users often rely on ridesharing services for daily travel, which present both challenges and opportunities for researchers interested in the accessible design of FAVs. The parallels between current BVI travel experiences in rideshares and predictions that FAV services will adopt rideshared models presents an enticing opportunity to use ridesharing as a proxy for understanding BVI needs in future FAV transportation. However, a key challenge is identifying the extent to which FAVs should be designed to provide the same assistance that human drivers currently provide for BVI travelers in rideshares. To address this issue, ridesharing users with visual impairment (n = 187) within the United States completed a survey instrument designed to assess and compare desires for interactions, information, and assistance between human operated and fully autonomous rideshare vehicles, as well as the modality of information delivery (auditory and/or haptic). Results indicate strong support for access to environmental information (e.g., spatial information about the destination) and contextual information (e.g., progress along the route) across the trip with automated vehicles via natural language interactions. Although results suggest significantly less desire for social interaction with the AI “at the wheel” of FAVs when compared to human drivers, findings indicate that participants desire some social collaboration and human-in-the-loop control during autonomous driving. By empirically comparing human and autonomous ridesharing and exploring both the information needs and modality preferences across information category, the study provides much-needed guidance for future design of humanlike, anthropomorphized, FAV AIs with important implications for social autonomous agents more generally. This study also speaks to the ways in which inclusive and accessible user interfaces should best support user needs across the range of vision loss in future transportation networks.

Keywords: Autonomous vehicles; People with visual impairment; Ridesharing; Accessible transportation; Social AI

Citation: Paul D.S. Fink, Maher Alsamsam, Justin R. Brown, Henry D. Kindler, Nicholas A. Giudice,
Give us something to chauffeur it: Exploring user needs in traditional and fully autonomous ridesharing for people who are blind or visually impaired, Transportation Research Part F: Traffic Psychology and Behaviour, Volume 98, 2023, Pages 91-103, ISSN 1369-8478, https://doi.org/10.1016/j.trf.2023.09.004.
(https://www.sciencedirect.com/science/article/pii/S1369847823001870)

The Autonomous Vehicle Assistant (AVA): Emerging technology design supporting blind and visually impaired travelers in autonomous transportation

aforbes — Thu, 10 Aug 2023 19:12:09 +0000

The U.S. Department of Transportation’s Inclusive Design Challenge spurred innovative research promoting accessible technology for people with disabilities in the future of autonomous transportation. This paper presents the user-driven design of the Autonomous Vehicle Assistant (AVA), a winning project of the challenge focused on solutions for people who are blind and visually impaired. Results from an initial survey (n = 90) and series of user interviews (n = 12) informed AVA’s novel feature set, which was evaluated through a formal navigation study (n = 10) and participatory design evaluations (n = 6). Aggregate findings suggest that AVA’s sensor fusion approach combining computer vision, last-meter assistance, and multisensory alerts provide critical solutions for users poised to benefit most from this emerging transportation technology.

Keywords: Autonomous vehicles, People with visual impairment, Accessibility

Citation: Paul D.S. Fink, Stacy A. Doore, Xue Lin, Matthew Maring, Pu Zhao, Aubree Nygaard, Grant Beals, Richard R. Corey, Raymond J. Perry, Katherine Freund, Velin Dimitrov, Nicholas A. Giudice, The Autonomous Vehicle Assistant (AVA): Emerging technology design supporting blind and visually impaired travelers in autonomous transportation,
International Journal of Human-Computer Studies, Volume 179, 2023, 103125, ISSN 1071-5819, https://doi.org/10.1016/j.ijhcs.2023.103125

Autonomous is Not Enough: Designing Multisensory Mid-Air Gestures for Vehicle Interactions Among People with Visual Impairments

aforbes — Thu, 10 Aug 2023 18:55:01 +0000

Should fully autonomous vehicles (FAVs) be designed inclusively and accessibly, independence will be transformed for millions of people experiencing transportation-limiting disabilities worldwide. Although FAVs hold promise to improve efficient transportation without intervention, a truly accessible experience must enable user input, for all people, in many driving scenarios (e.g., to alter a route or pull over during an emergency). Therefore, this paper explores desires for control in FAVs among (n=23) people who are blind and visually impaired. Results indicate strong support for control across a battery of driving tasks, as well as the need for multimodal information. These findings inspired the design and evaluation of a novel multisensory interface leveraging mid-air gestures, audio, and haptics. All participants successfully navigated driving scenarios using our gestural-audio interface, reporting high ease-of-use. Contributions include the first inclusively designed gesture set for FAV control and insight regarding supplemental haptic and audio cues.

Keywords: Spatial audio, Accessible design, Gestures, Autonomous vehicles, Interfaces for blind or visually impaired individuals, Situational awareness

Citation: Paul D. S. Fink, Velin Dimitrov, Hiroshi Yasuda, Tifany L. Chen, Richard R. Corey, Nicholas A. Giudice, and Emily S. Sumner. 2023. Autonomous is Not Enough: Designing Multisensory Mid-Air Gestures for Vehicle Interactions Among People with Visual Impairments . In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), April 23– 28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 13 pages. https: //doi.org/10.1145/3544548.3580762 International, USA. DOI: http://doi.org/10.54941/ahfe1003586

Download PDF

Experimental Evaluation of Multi-scale Tactile Maps Created with SIM, a Web App for Indoor Map Authoring

eblackwood — Mon, 15 May 2023 15:01:46 +0000

In this article, we introduce Semantic Interior Mapology (SIM), a web app that allows anyone to quickly trace the floor plan of a building, generating a vectorized representation that can be automatically converted into a tactile map at the desired scale. The design of SIM is informed by a focus group with seven blind participants. Maps generated by SIM at two different scales have been tested by a user study with 10 participants, who were asked to perform a number of tasks designed to ascertain the spatial knowledge acquired through map exploration. These tasks included cross-map pointing and path finding, and determination of turn direction/walker orientation during imagined path traversal. By and large, participants were able to successfully complete the tasks, suggesting that these types of maps could be useful for pre-journey spatial learning.

Multimodality as universality: Designing inclusive accessibility to graphical information

eblackwood — Wed, 10 May 2023 19:00:27 +0000

Graphical representations are ubiquitous in the learning and teaching of science, technology, engineering, and mathematics (STEM). However, these materials are often not accessible to the over 547,000 students in the United States with blindness and significant visual impairment, creating barriers to pursuing STEM educational and career pathways. Furthermore, even when such materials are made available to visually impaired students, access is likely through literalized modes (e.g., braille, verbal description), which is problematic as these approaches (1) do not directly convey spatial information and (2) are different from the graphic-based materials used by students without visual impairment. The purpose of this study was to design and evaluate a universally accessible system for communicating graphical representations in STEM classes. By combining a multisensory vibro-audio interface and an app running on consumer mobile hardware, the system is meant to work equally well for all students, irrespective of their visual status. We report the design of the experimental system and the results of an experiment where we compared learning performance with the system to traditional (visual or tactile) diagrams for sighted participants (n = 20) and visually impaired participants (�� = 9) respectively. While the experimental multimodal diagrammatic system (MDS) did result in significant learning gains for both groups of participants, the results also revealed no statistically significant differences in the capacity for learning from graphical information across both comparison groups. Likewise, there were no statistically significant differences in the capacity for learning from graphical information between the stimuli presented through the experimental system and the traditional (visual or tactile) diagram control conditions, across either participant group. These findings suggest that both groups were able to learn graphical information from the experimental system as well as traditional diagram presentation materials. This learning modality was supported without the need for conversion of the diagrams to make them accessible for participants who required tactile materials. The system also provided additional multisensory information for sighted participants to interpret and answer questions about the diagrams. Findings are interpreted in terms of new universal design principles for producing multisensory graphical representations that would be accessible to all learners.

Designing mobile spatial navigation systems from the user’s perspective: an interdisciplinary review

eblackwood — Fri, 06 May 2022 15:48:25 +0000

Navigation systems have become increasingly available and more complex over the past few decades as maps have changed from largely static visual and paper-based representations to interactive and multimodal computerized systems. In this introductory article to the Special Issue on Human-computer Interaction, Geographic Information, and Navigation, we review literature across a variety of fields to generate nine design principles to guide future research and development of navigation systems. Specifically, we suggest making mobile navigation systems more accessible and multimodal, which will make the systems more inclusive and usable for all types of users. We also introduce the research articles contributed to the present special issue and suggest future research directions to empirically evaluate emerging and untested features of user-adapted and context-aware mobile navigation systems.

Download pdf

Citation:

Ian Ruginski, Nicholas Giudice, Sarah Creem-Regehr & Toru Ishikawa (2022): Designing mobile spatial navigation systems from the user’s perspective: an interdisciplinary review, Spatial Cognition & Computation, DOI: 10.1080/13875868.2022.2053382