Driving Simulators for the Evaluation of Human-Machine Interfaces in Assisted and Automated Vehicles

2021 ◽  
Author(s):  
Thomas McWilliams ◽  
Bruce Mehler ◽  
Bobbie Seppelt ◽  
Bryan Reimer

Driving simulator validation is an important and ongoing process. Advances in in-vehicle human machine interfaces (HMI) mean there is a continuing need to reevaluate the validity of use cases of driving simulators relative to real world driving. Along with this, our tools for evaluating driver demand are evolving, and these approaches and measures must also be considered in evaluating the validity of a driving simulator for particular purposes. We compare driver glance behavior during HMI interactions with a production level multi-modal infotainment system on-road and in a driving simulator. In glance behavior analysis using traditional glance metrics, as well as a contemporary modified AttenD measure, we see evidence for strong relative validity and instances of absolute validity of the simulator compared to on-road driving.


Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 386 ◽  
Author(s):  
Lars Kooijman ◽  
Riender Happee ◽  
Joost de Winter

In future trac, automated vehicles may be equipped with external human-machine interfaces (eHMIs) that can communicate with pedestrians. Previous research suggests that, during first encounters, pedestrians regard text-based eHMIs as clearer than light-based eHMIs. However, in much of the previous research, pedestrians were asked to imagine crossing the road, and unable or not allowed to do so. We investigated the effects of eHMIs on participants’ crossing behavior. Twenty-four participants were immersed in a virtual urban environment using a head-mounted display coupled to a motion-tracking suit. We manipulated the approaching vehicles’ behavior (yielding, nonyielding) and eHMI type (None, Text, Front Brake Lights). Participants could cross the road whenever they felt safe enough to do so. The results showed that forward walking velocities, as recorded at the pelvis, were, on average, higher when an eHMI was present compared to no eHMI if the vehicle yielded. In nonyielding conditions, participants showed a slight forward motion and refrained from crossing. An analysis of participants’ thorax angle indicated rotation towards the approaching vehicles and subsequent rotation towards the crossing path. It is concluded that results obtained via a setup in which participants can cross the road are similar to results from survey studies, with eHMIs yielding a higher crossing intention compared to no eHMI. The motion suit allows investigating pedestrian behaviors related to bodily attention and hesitation.


Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 173 ◽  
Author(s):  
Christina Kaß ◽  
Stefanie Schoch ◽  
Frederik Naujoks ◽  
Sebastian Hergeth ◽  
Andreas Keinath ◽  
...  

Research on external human–machine interfaces (eHMIs) has recently become a major area of interest in the field of human factors research on automated driving. The broad variety of methodological approaches renders the current state of research inconclusive and comparisons between interface designs impossible. To date, there are no standardized test procedures to evaluate and compare different design variants of eHMIs with each other and with interactions without eHMIs. This article presents a standardized test procedure that enables the effective usability evaluation of eHMI design solutions. First, the test procedure provides a methodological approach to deduce relevant use cases for the evaluation of an eHMI. In addition, we define specific usability requirements that must be fulfilled by an eHMI to be effective, efficient, and satisfying. To prove whether an eHMI meets the defined requirements, we have developed a test protocol for the empirical evaluation of an eHMI with a participant study. The article elucidates underlying considerations and details of the test protocol that serves as framework to measure the behavior and subjective evaluations of non-automated road users when interacting with automated vehicles in an experimental setting. The standardized test procedure provides a useful framework for researchers and practitioners.


Author(s):  
Koen de Clercq ◽  
Andre Dietrich ◽  
Juan Pablo Núñez Velasco ◽  
Joost de Winter ◽  
Riender Happee

Objective: In this article, we investigated the effects of external human-machine interfaces (eHMIs) on pedestrians’ crossing intentions. Background: Literature suggests that the safety (i.e., not crossing when unsafe) and efficiency (i.e., crossing when safe) of pedestrians’ interactions with automated vehicles could increase if automated vehicles display their intention via an eHMI. Methods: Twenty-eight participants experienced an urban road environment from a pedestrian’s perspective using a head-mounted display. The behavior of approaching vehicles (yielding, nonyielding), vehicle size (small, medium, large), eHMI type (1. baseline without eHMI, 2. front brake lights, 3. Knightrider animation, 4. smiley, 5. text [WALK]), and eHMI timing (early, intermediate, late) were varied. For yielding vehicles, the eHMI changed from a nonyielding to a yielding state, and for nonyielding vehicles, the eHMI remained in its nonyielding state. Participants continuously indicated whether they felt safe to cross using a handheld button, and “feel-safe” percentages were calculated. Results: For yielding vehicles, the feel-safe percentages were higher for the front brake lights, Knightrider, smiley, and text, as compared with baseline. For nonyielding vehicles, the feel-safe percentages were equivalent regardless of the presence or type of eHMI, but larger vehicles yielded lower feel-safe percentages. The Text eHMI appeared to require no learning, contrary to the three other eHMIs. Conclusion: An eHMI increases the efficiency of pedestrian-AV interactions, and a textual display is regarded as the least ambiguous. Application: This research supports the development of automated vehicles that communicate with other road users.


Author(s):  
Tatsuru Daimon ◽  
◽  
Masahiro Taima ◽  
Satoshi Kitazaki

To determine whether external human–machine interfaces (eHMIs) make pedestrians careless toward the traffic environment, we examined the following four hypotheses: H1, the pedestrian decides to cross earlier after seeing a yielding message on an eHMI; H2, the pedestrian perceives safety after seeing a yielding message on an eHMI; H3, the pedestrian’s confirming behavior before crossing is suppressed after the pedestrian sees a yielding message on an eHMI; H4, miscommunication between pedestrians and automatic vehicles can be caused by yielding messages on an eHMI.


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