Takeover requests for automated driving: The effects of signal direction, lead time, and modality on takeover performance

Huang, Gaojian; Pitts, Brandon J.

doi:10.1016/j.aap.2021.106534

Cited by 44 publications

(12 citation statements)

References 42 publications

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“…In some instances, however, older drivers demonstrated response times comparable to those of younger drivers [28]. In addition, research indicates that older drivers tend to focus more on the road and less on secondary tasks [29]. The third area of study focuses on cross-modality comparisons.…”

Section: Takeover Request and Modalitymentioning

confidence: 99%

“…They are more likely to experience a decline in cognitive function that can affect their ability to safe operate a motor vehicle, and accident rates increase after age 65. In the study of Huang and Pitts, they used multiple visual, auditory, and tactile stimuli as TOR cues and found that younger adults had faster brake reaction times when using single visual and auditory stimuli compared to older adults [29]. However, tactile signal did not make a difference.…”

Section: Individual Differences In Drivingmentioning

confidence: 99%

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Individual Differences in Signal Perception for Takeover Request in Autonomous Driving

Lee

Kang

2023

Applied Sciences

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In the context of partial autonomy, where autonomous vehicles and humans share control of the vehicle, bringing out-of-the-loop drivers back into the loop is a significant challenge. While warning signal design guidelines are commonly used to provide alerts, few studies have examined each signal in depth with an emphasis on the autonomous environment. This study aims to fill this gap by investigating visual, auditory, and tactile stimuli and modifying their sub-attributes to explore variations related to age, gender, and other individual backgrounds. For this objective, the research examined the correlations between age, gender, and individual backgrounds with reaction times to TOR signals, investigating the effects of sub-attribute variations on participants’ responses and exploring the subjective evaluations of the signals. A driving simulator was utilized to create a realistic driving environment and measure participants’ reaction times in takeover request situations. Analysis of the data revealed correlations between age and reaction times for auditory and tactile signals, with interaction effects observed between age and sub-attribute intensity. Additionally, participants exhibited varying reaction time patterns in response to different sub-attribute intensities. By evaluating individual differences in perception based on modality characteristics, often overlooked in prior research, this study serves as a foundational contribution to future research in the field.

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Section: Takeover Request and Modalitymentioning

confidence: 99%

Section: Individual Differences In Drivingmentioning

confidence: 99%

Individual Differences in Signal Perception for Takeover Request in Autonomous Driving

Lee

Kang

2023

Applied Sciences

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“…Tactile displays, which have been used as takeover requests (TORs) in automated vehicles, have also been associated with shorter takeover times and higher subjective/satisfaction ratings compared to visual and auditory displays alone (Huang & Pitts, 2022). The impact of tactile interfaces on task and signal response performance can depend on various parameters, such as intensity and location (e.g., Giang et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Tactile Displays: The Effects of Location and Intensity on Automated Vehicle Takeover Performance

Huang,

Pitts

2023

Proceedings of the Human Factors and Ergonomics Society Annual

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This study investigated the effects of tactile display location and intensity on automated vehicle takeover performance. Twenty participants completed simulated driving tasks in a Level 3 automated vehicle and responded to takeover requests presented at different locations (seat back, seat pan, seat belt, and wrist) with different intensity levels. Results showed that higher intensity tactile displays were associated with faster takeover times, and placing the display on the wrist was correlated with shorter takeover times compared to the seat pan in lower intensity. However, there were no significant effects on maximum resulting jerk. These findings suggest that incorporating tactile displays in automated vehicles as takeover requests is promising, particularly when placed on the wrist and presented at higher intensities. This research contributes to the development of human-machine interfaces that can better assist drivers during takeovers and improve the safety of automated vehicles.

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“…1) entails first 31 perceiving and processing the takeover request and then need-32 ing to quickly shift their attention while becoming aware of 33 their surroundings and assessing the situation, then moving 34 their hands and feet back to the driving position to manually 35 FIGURE 1. The Takeover Model ( [3]; adapted from [6]).…”

mentioning

confidence: 99%

“…takeover control of the vehicle, in an effort to execute a strategic steering/maneuvering decision, under a short vital period of time [3], [4], [5], [6].…”

mentioning

confidence: 99%

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

Martinez

Huang

2022

IEEE Access

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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' 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.INDEX TERMS Human-machine interface, tactile displays, automated driving, takeover request. I. INTRODUCTION 19 Autonomous vehicles come with great benefits, such as 20 are engaging in non-driving-related tasks (NDRTs) such as 40 reading or texting at the time of takeover, which could lead 41 to higher cognitive workload and longer reaction times to 42 takeover requests and potential threats [7], [8] and can ulti-43 mately result in a driver's possible failure to successfully 44 take over. The criticality of this process could then be further 45 exacerbated when sensory information in the driving environ-46 ment is overwhelming, leading to an overload in the drivers' 47 sensory channels. For example, drivers need to reorient (pay 48 attention to the road) and regain situation awareness during 49 the takeover process [6], [9], [10]. However, a takeover in 50 complex environments such as urban areas that are already 51 filled with a plethora of visual and auditory information 52 to be perceived and processed, e.g., the status/location of 53 surrounding/oncoming obstacles/objects, including but not 54 limited to vehicles, pedestrians, traffic signs/signals, all of 55 which may lead to the overstimulation of a drivers' visual 56 and auditory resources. There lies a need for a reliable 57 human-machine interface (HMI) that utilizes idle sens...

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Takeover requests for automated driving: The effects of signal direction, lead time, and modality on takeover performance

Cited by 44 publications

References 42 publications

Individual Differences in Signal Perception for Takeover Request in Autonomous Driving

Individual Differences in Signal Perception for Takeover Request in Autonomous Driving

Tactile Displays: The Effects of Location and Intensity on Automated Vehicle Takeover Performance

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

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