In-Vehicle Human Machine Interface: Investigating the Effects of Tactile Displays on Information Presentation in Automated Vehicles

Background: Semi-autonomous vehicles still require human drivers to take over when the automated systems can no longer perform the driving task. Objective: The goal of this study was to design and test the effects of six meaningful tactile signal types, representing six driving scenarios (i.e., navigation, speed, surrounding vehicles, over the speed limit, headway reductions, and pedestrian status) respectively, and two pattern durations (lower and higher urgencies), on drivers\u27 perception and performance during automated driving. Methods: Sixteen volunteers participated in an experiment utilizing a medium-fidelity driving simulator presenting vibrotactile signals via 20 tactors embedded in the seat back, pan, and belt. Participants completed four separate driving sessions with 30 tactile signals presented randomly throughout each drive. Reaction times (RT), interpretation accuracy, and subjective ratings were measured. Results: Results illustrated shorter RTs and higher intuitive ratings for higher urgency patterns than lower urgency patterns. Pedestrian status and headway reduction signals were associated with shorter RTs and increased confidence ratings, compared to other tactile signal types. Lastly, among six tactile signals, surrounding vehicle and navigation signal types had the highest interpretation accuracy. Conclusion: These results will be used as preliminary data for future studies that aim to investigate the effects of meaningful tactile displays on automated vehicle takeover performance in complex situations (e.g., urban areas) where actual takeovers are required. The findings of this study will inform the design of next-generation in-vehicle human-machine interfaces

Exploring the Effects of Meaningful Tactile Display on Perception and Preference in Automated Vehicles

There is an existing issue in human-machine interaction, such that drivers of semi-autonomous vehicles are still required to take over control of the vehicle during system limitations. A possible solution may lie in tactile displays, which can present status, direction, and position information while avoiding sensory (e.g., visual and auditory) channels overload to reliably help drivers make timely decisions and execute actions to successfully take over. However, limited work has investigated the effects of meaningful tactile signals on takeover performance. This study synthesizes literature investigating the effects of tactile displays on takeover performance in automated vehicles and conducts a human-subject study to design and test the effects of six meaningful tactile signal types and two pattern durations on drivers’ perception and performance during automated driving. The research team performed a literature review of 18 articles that conducted human-subjects experiments on takeover performance utilizing tactile displays as takeover requests. Takeover performance in these studies were highlighted, such as response times, workload, and accuracy. The team then conducted a human-subject experiment, which included 16 participants that used a driving simulator to present 30 meaningful vibrotactile signals, randomly across four driving sessions measuring for reaction times (RTs), interpretation accuracy, and subjective ratings. Results from the literature suggest that tactile displays can present meaningful vibrotactile patterns via various in-vehicle locations to help improve drivers’ performance during the takeover and can be used to assist in the design of human-machine interfaces (HMI) for automated vehicles. The experiment yielded results illustrating higher urgency patterns were associated with shorter RTs and higher intuitive ratings. Also, pedestrian status and headway reduction signals presented shorter RTs and increased confidence ratings compared to other tactile signal types. Finally, the signal types that yielded the highest accuracy were the surrounding vehicle and navigation signal types. Implications of these findings may lie in informing the design of next-generation in-vehicle HMIs and future human factors studies on human-automation interactions

Influence of normal stress on the shear strength of the structural plane considering the size effect

The shear strength of a structural plane is a critical parameter in the analysis of engineering rock stability. Significant differences exist due to the various normal stresses in the structural plane. Therefore, evaluating the rock deformation to effectively determine the influence of normal stresses at different scales on the shear strength of structural planes is of great significance. This study discusses the effects of normal stress and structural plane size on shear strength through numerical simulations and regression analysis. The results showed that the shear strength of the structural plane increases linearly with increasing normal stress. The shear strength of the structural plane decreases with increasing size, and the corresponding curve is exponential. The characteristic size and shear strength increase linearly with increasing normal stress. This paper presents the concrete form of these relationships, which can be used to calculate and predict the shear strength, which has significance in guiding engineering

Exploring the Use of Public Transportation Among Older Adults During the COVID-19 Pandemic: A National Survey

Public transportation is an essential part of many older adults’ lives, but the pandemic presented new challenges for the vulnerable population. Adults aged 65 years and older experienced additional challenges, such as limited mobility options (e.g., lack of buses or trains in service due a combination of government lockdowns, fear of contracting or spreading the virus, and driver shortages in certain areas) because of the pandemic, which may have resulted in more age-related declines in perceptual, cognitive, and physical functioning. This study explores how older adults living in major metropolitan cities in the United States used and perceived public transportation during the COVID-19 pandemic. The research team conducted an online survey through the Amazon Mechanical Turk (MTurk) crowdsourcing marketplace, a platform that offers opportunities to recruit a larger number of participants from diverse geographic locations. 260 respondents completed the survey. Eligibility included: (1) residing in the United States, (2) being aged 55 years or older (the oldest age that can be selected on MTurk), and (3) having an approval rating of 90% or above (i.e., the percentage of the workers’ submitted tasks approved by survey requesters, offered by the MTurk platform). Overall, older adults reported that they had changed travel patterns since the onset of the COVID-19 pandemic, experienced challenges in using public transportation, and expressed concerns about catching the SARS-CoV-2 virus while using public transportation. Mobile technology (e.g., a transportation navigation app) was perceived as a good option for finding public transportation information, but needs improved user experience and accessibility. These findings may help transit agencies develop effective strategies for improving transportation services and increasing policymakers’ awareness of older adults’ need for accessible public transportation

Exploring the Use of Public Transportation Among Older Adults During the COVID-19 Pandemic: A National Survey [Research Brief]

69A3551747127Public transportation is an essential part of many older adults\u2019 lives, but the pandemic presented new challenges for the vulnerable population. Adults aged 65 years and older experienced additional challenges, such as limited mobility options (e.g., lack of buses or trains in service due a combination of government lockdowns, fear of contracting or spreading the virus, and driver shortages in certain areas) because of the pandemic, which may have resulted in more age-related declines in perceptual, cognitive, and physical functioning. This study explores how older adults living in major metropolitan cities in the United States used and perceived public transportation during the COVID-19 pandemic

Exploring the Use of Public Transportation Among Older Adults During the COVID-19 Pandemic: A National Survey [Report]

69A3551747127Public transportation is an essential part of many older adults\u2019 lives, but the pandemic presented new challenges for the vulnerable population. Adults aged 65 years and older experienced additional challenges, such as limited mobility options (e.g., lack of buses or trains in service due a combination of government lockdowns, fear of contracting or spreading the virus, and driver shortages in certain areas) because of the pandemic, which may have resulted in more age-related declines in perceptual, cognitive, and physical functioning. This study explores how older adults living in major metropolitan cities in the United States used and perceived public transportation during the COVID-19 pandemic. The research team conducted an online survey through the Amazon Mechanical Turk (MTurk) crowdsourcing marketplace, a platform that offers opportunities to recruit a larger number of participants from diverse geographic locations. 260 respondents completed the survey. Eligibility included: (1) residing in the United States, (2) being aged 55 years or older (the oldest age that can be selected on MTurk), and (3) having an approval rating of 90% or above (i.e., the percentage of the workers\u2019 submitted tasks approved by survey requesters, offered by the MTurk platform). Overall, older adults reported that they had changed travel patterns since the onset of the COVID-19 pandemic, experienced challenges in using public transportation, and expressed concerns about catching the SARS-CoV-2 virus while using public transportation. Mobile technology (e.g., a transportation navigation app) was perceived as a good option for finding public transportation information, but needs improved user experience and accessibility. These findings may help transit agencies develop effective strategies for improving transportation services and increasing policymakers\u2019 awareness of older adults\u2019 need for accessible public transportation

Automated Speech Recognition Technology to Support in Flight Weather-Related Communication for GA Pilots

Weather information latency during flight in general aviation (GA) has resulted in numerous incidents. Hands-free automated speech recognition (ASR) systems have the potential to help overcome this challenge and facilitate rapid weatherrelated information exchange. However, it is unclear to what extent ASR systems can support pilot communication in such noisy environments. The goals of this study were to (1) evaluate the performance of 7 commercially-available ASR systems to recognize weather phrases during GA operations and (2) determine whether speech-to-noise (S/N) ratio, flight phase, and accent type modulate system performance. Overall, the highest accuracy percentage achieved by any system was 72%, when the S/N ratio was at least 3/2. This research can help to inform the selection and development of next-generation technologies to be used in safety-critical, information-rich domains