Co-authored with Guy Cohen-Lazry, to appear in Technology in Society.
Is staying out of bomb-shelters a human-automation interaction issue?http://dx.doi.org/10.1016/j.techsoc.2016.08.002
“Iron-Dome” is an anti-rocket air defense system placed around major urban areas of Israel. It was created to provide citizens with greater deal of protection against hostile rocket attacks. A study was conducted to examine whether civilians’ experience with the “Iron-Dome” system affects people’s perceived reliability of it, their trust in it, and their complacency to hostile rocket alerts. During the 2014 Israel-Gaza conflict (operation “Protective Edge”), an online questionnaire was used to measure civilian respondents’ perceptions and actions. Results indicated that people living in geographical areas who had more experience with rocket attacks and thereby with the “Iron-Dome” system, perceived it as less reliable, had lower trust in it, and were less complacent. These results show that people’s interaction with the “Iron-Dome” corresponds to the common prediction of theoretical models of human-automation interaction. This understanding may assist in planning of implementation programs and guidance of civilians for other mass protection systems in the future.
Key words: Iron-Dome, Complacency, Trust in automation, Experience, Rocket defense system.
Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure?
Background: Traffic safety is often expressed as the ‘inverse of accidents’. However, it is
more than the mere absence of accidents. Past studies often looked for associations
between accidents and self-reports like the Driver Behaviour Questionnaire
(DBQ; Reason, Manstead, Stradling, Baxter, & Campbell, 1990). The focus in this study
changed from counting accidents to quantifying unsafe acts as violations. The objective
was to show that drivers’ specific violations can be traced to personal characteristics such
as sensation seeking (SSS-V; Zuckerman, 1994), gender role (BSRI; Bem sex role inventory,
Bem, 1974), demographics, and driving exposure.
Method: A web-based questionnaire was distributed, integrating several known questionnaires.
Five hundred and twenty-seven questionnaires were completed and analyzed.
Results: Sensation seeking, gender role, experience, and age predicted respondents’ score
on the DBQ, as well as the interaction of sensation seeking with gender and gender role.
Gender role was a more valid predictor of driver behavior than gender.
Conclusions: The effect of gender role on drivers’ self-reported violation tendency is the
most interesting and the most intriguing finding of this survey and indicates the need to
further examine gender role affects in driving.
HCI International 2016 17 – 22 July 2016
Shanne Honig will be presenting a poster on an experiment that we conducted as part of our ‘Follow Me’ research: Proxemics and Responsiveness Preferences of Elderly Users in a Person-Following Robot.
This is our most recent publication, accepted for publication in Safety Science.
Please cite this article in press as: Tapiro, H., et al. Cell phone conversations and child pedestrian’s crossing behavior; a simulator study. Safety Sci. (2016), http://dx.doi.org/10.1016/j.ssci.2016.05.013
Cell phone conversations and child pedestrian’s crossing behavior; a simulator study
Hagai Tapiro, Yisrael Parmet and Tal Oron-Gilad
Child pedestrians are highly represented in fatal and severe road crashes and differ in their crossing behavior from adults. Although many children carry cell phones, the effect that cell phone conversations have on children’s crossing behavior has not been thoroughly examined. A comparison of children and adult pedestrians’ crossing behavior while engaged in cell phone conversations was conducted. In a semi-immersive virtual environment simulating a typical city, 14 adults and 38 children (11 children aged 7-8; 18 aged 9-10 and 9 aged 11-13), experienced road crossing related traffic-scene scenarios. They were requested to press a response button whenever they felt it was safe to cross. Eye movements were tracked. Results have shown that all age groups’ crossing behaviors were affected by cell phone conversations. When busy with more cognitively demanding conversation types, participants were slower to react to a crossing opportunity, chose smaller crossing gaps, and allocated less visual attention to the peripheral regions of the scene. The ability to make better crossing decisions improved with age, but no interaction with cell phone conversation type was found. The most prominent improvement was shown in ‘safety gap’; each age group maintained a longer gap than its predecessor younger age group. In accordance to the current study, it is safe to say that cell phone conversations can hinder child and adult pedestrians’ safety. Thereby, it is important to take those findings in account when aiming to train young pedestrians for road-safety and increase public awareness.
Interested in seeing an interactive visualization app of our data?https://eyemove.shinyapps.io/cell-phone/
Two of our works have been accepted as full papers for presentation and publication in the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2016).
“Postures of a Robot Arm – window to robot intentions?” authored by my doctoral student Sridatta Chaterjee and co-authored by my colleagues Drs. Oren Shriki and Idit Shalev.
Abstract— Body language of robot arms, have rarely been explored as a medium of conveying robot intentions. An exploratory study was done focusing on two questions: one, if robot arm postures can convey robot intentions, and two, if participants coming in contact with this robot arm for the first time can associate any meaning to the postures without watching the robot in action, or working with it. Thirty five participants of a wide age range (25-70) took part in this exploratory study. Results show that participants could interpret some postures. Four distinct types of postures have been selected to four separate categories by the majority of participants irrespective of their age. In addition, postures selected in categories like, ‘Robot giving object in a friendly manner’; ‘Robot is saying Hi!’, ‘Robot has been told not to disturb’ show similarity to body language exhibited by humans and animals while communicating such messages.
“The Influence of Following Angle on Performance Metrics of a Human-Following Robot” co-authored by our graduate students Shanee Honig and Dror Katz, and my colleague Prof. Yael Edan.
Abstract— Robots that operate alongside people need to be able to move in socially acceptable ways. As a step toward this goal, we study how and under which circumstances the angle at which a robot follows a person may affect the human experience and robot tracking performance. In this paper, we aimed to assess three following angles (0◦ angle, 30◦ angle, and 60◦ angle) under two conditions: when the robot was carrying a valuable personal item or not. Objective and subjective indicators of the quality of following and participants’ perceptions and preferences were collected. Results indicated that the personal item manipulation increased awareness to the quality of the following and the following angles. Without the manipulation, participants were indifferent to the behavior of the robot. Our following algorithm was successful for tracking at a 0◦ and 30◦ angle, yet it must be improved for wider angles. Further research is required to obtain better understanding of following angle preferences for varying environment and task conditions.
NY, Looking forward to two great presentations!
Human-following capabilities of robots may become important in assistive robotic applications to facilitate many daily tasks (e.g. carrying personal items or groceries). Robot’s following distance, following angle and acceleration influence the quality of the interaction between the human and the robot by impacting walking efficiency (e.g., pace, flow and unwanted stops), user comfort and robot likability.
Our team gave a presentation at the ICR 2016 conference focusing on Subjective preferences regarding human-following robots: preliminary evidence from laboratory experiments.
- This research effort is led by our graduate student Shanee Honig
- For the person-tracking and following algorithm (Dror Katz & Yael Edan, work in progress) we use the Pioneer LX Robot’s built in camera and a Microsoft Kinect.
- Currently we focus on 3 angles of following: back following (0 degree angle), a 30 degree angle, and a 60 degree angle.
- We use a personal item manipulation (e.g., wallet) to examine how participants engage with the robot. Naturally when participants place a personal item on the robot, they become more engaged with it.
- Come see us at the HCII 2016 where we will present a poster on sensitivity of older users (68 and above) to the quality of interaction, depending on robot’s following distance and acceleration, and the context of walk – Follow Me: Proxemics and Responsiveness Preferences of Older Users in a Human-Following Robot.
At last, a new publication in frontiers in Psyhcology co authored with Talya Porat, Michal Rottem-Hovev and Jacob Silbiger (Synergy Integration).
In this article we conduct a retrospective examination of studies concerned with man-UAS ratio, i.e., how many systems should a single operator control, should a team share (multiple operator – multiple UASs; MOMU).
Proliferation in the use of Unmanned Aerial Systems (UASs) in civil and military operations has presented a multitude of human factors challenges; from how to bridge the gap between demand and availability of trained operators, to how to organize and present data in meaningful ways. Utilizing the Design Research Methodology (DRM), a series of closely related studies with subject matter experts (SMEs) demonstrate how the focus of research gradually shifted from “how many systems can a single operator control” to “how to distribute missions among operators and systems in an efficient way”. The first set of studies aimed to explore the modal number, i.e., how many systems can a single operator supervise and control. It was found that an experienced operator can supervise up to 15 UASs efficiently using moderate levels of automation, and control (mission and payload management) up to 3 systems. Once this limit was reached, a single operator’s performance was compared to a team controlling the same number of systems. In general, teams led to better performances. Hence, shifting design efforts towards developing tools that support teamwork environments of multiple operators with multiple UASs (MOMU). In MOMU settings, when the tasks are similar or when areas of interest overlap, one operator seems to have an advantage over a team who needs to collaborate and coordinate. However, in all other cases, a team was advantageous over a single operator.