The theory of affordances

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.

/pdf/external-human-machine-interfaces-on-automated-vehicles-1y8pv05y47.pdf

External human-machine interfaces on automated vehicles: Effects on pedestrian crossing decisions

Efficacy of virtual reality in pedestrian safety research.

Many companies aim for delivering systems for autonomous driving reaching out for SAE Level 5. As these systems run much more complex software than typical premium cars of today, a thorough testing strategy is needed. Early prototyping of such systems can be supported using recorded data from on-board and surrounding sensors as long as open-loop testing is applicable; later, though, closed-loop testing is necessary—either by testing on the real vehicle or by using a virtual testing environment. This paper is a substantial extension of our work presented at the 2017 IEEE International Conference on Intelligent Transportation Systems (ITSC) that was surveying the area of publicly available driving datasets. Our previous results are extended by additional datasets and complemented with a summary of publicly available virtual testing environments to support closed-loop testing. As such, a steadily growing number of 37 datasets for open-loop testing and 22 virtual testing environments for closed-loop testing have been surveyed in detailed. Thus, conducting research toward autonomous driving is significantly supported from complementary community efforts: A growing number of publicly accessible datasets allow for experiments with perception approaches or training and testing machine-learning-based algorithms, while virtual testing environments enable end-to-end simulations.

/pdf/test-your-self-driving-algorithm-an-overview-of-publicly-54xlrlptis.pdf

Test Your Self-Driving Algorithm: An Overview of Publicly Available Driving Datasets and Virtual Testing Environments

Pedestrian distraction: The effects of road environment complexity and age on pedestrian's visual attention and crossing behavior.

This paper presents an experiment conducted in a large-screen immersive virtual environment to evaluate how texting pedestrians respond to permissive traffic alerts delivered via their cell phone. We developed a cell phone app that delivered information to texting pedestrians about when traffic conditions permit safe crossing. We compared gap selection and movement timing in three groups of pedestrians: texting, texting with alerts, and no texting (control). Participants in the control and alert groups chose larger gaps and were more discriminating in their gap choices than participants in the texting group. Both the control and alert groups had more time to spare than the texting group when they exited the roadway even though the alert group timed their entry relative to the lead car less tightly than the control and texting groups. By choosing larger gaps, participants in the alert group were able to compensate for their poorer timing of entry, resulting in a margin of safety that did not differ from those who were not texting. However, they also relied heavily on the alert system and paid less attention to the roadway. The discussion focuses on the potential of assistive technologies based on Vehicle-to-Pedestrian (V2P) communications technology for mitigating pedestrian-motor vehicle crashes.

Using a virtual environment to study the impact of sending traffic alerts to texting pedestrians

We investigated how two people jointly coordinate their decisions and actions in a co-occupied, large-screen virtual environment. The task for participants was to physically cross a virtual road with continuous traffic without getting hit by a car. Participants performed this task either alone or with another person (see Fig.1). We found that pairs often crossed the same gap together and closely synchronized their movements when crossing. Pairs also chose larger gaps than individuals to accommodate the extra time needed to cross through gaps together. These results reveal how two people interact and coordinate their behaviors in performing whole-body, joint motions. This study also provides a foundation for future studies examining joint actions in shared VEs where participants are represented by graphic avatars.

Acting together: Joint pedestrian road crossing in an immersive virtual environment

We investigated how people jointly coordinate their decisions and actions with a computer-generated character (agent) in a large-screen virtual environment. The task for participants was to physically cross a steady stream of traffic on a virtual road without getting hit by a car. Participants performed this task with another person or with a computer-generated character (Fig. 1). The character was programmed to be either safe (taking only large gaps) or risky (also taking relatively small gaps). We found that participants behaved in many respects similarly with real and virtual partners. They maintained similar distances between themselves and their partner, they often crossed the same gap with their partner, and they synchronized their crossing with their partner. We also found that the riskiness of the character influenced the gap choices of participants. This study demonstrates the potential for using large-screen virtual environments to study how people interact with CG characters when performing whole-body joint actions.

https://dl.acm.org/doi/pdf/10.1145/2931002.2931003

Action coordination with agents: crossing roads with a computer-generated character in a virtual environment

This paper investigates the influence of stereoscopic vs. non-stereoscopic display in large-screen virtual environments on an everyday perception-action task - crossing traffic-filled roadways as a pedestrian. The task for participants was to physically cross a virtual road with continuous traffic without getting hit by a car in a CAVE-like virtual environment. Half of the participants performed the task with stereoscopic display and half performed the task with non-stereoscopic display. We found that stereoscopic display had little impact on the size of the gaps participants crossed or the timing of their crossing motion relative to the gap with the exception of a small difference in crossing speed. The results are important for validating the use of non-stereoscopic image displays in ground vehicle simulation and supporting the use of non-stereoscopic displays for multi-viewpoint rendering in co-occupied virtual environments.

https://dl.acm.org/doi/pdf/10.1145/3119881.3119886

The influence of stereoscopic image display on pedestrian road crossing in a large-screen virtual environment

Vehicle-to-Pedestrian (V2P) Communications Technology: Do Cell Phone Warnings Improve Road-Crossing Safety for Texting Pedestrians?

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