1. The Effect of Texting Using a Head Mounted Display on Brake
Reaction Time and Time Headway
Kyle Walter
Human Systems Engineering, Arizona State University
2. Abstract
Previous research on the effect of smartphone use on user distraction has
primarily focused on phone calls and various forms of texting. As technology
progresses, drivers are now able to use HMD (head-mounted displays) and other
hands-free devices. HMDs allow users to have their eyes directed to the road, however
open the user to inattentional blindness and give them a false sense of security. The
present study compared the effects of two smartphone tasks and two Head Mounted
Display (HMD) tasks on car following performance in a driving simulator. Simulation
tasks were chosen across two factors: Devices used (Smartphone vs. HMD) and
Condition of the Participant (Distracted vs. Not Distracted). Brake Reaction Times (BRT)
were significantly slower in the condition in which the user had to text off of the HMD
when compared to the Baseline condition (p=.004) and moderately significant when
compared to the Texting condition (p=.059). Although there are many applications that
might help users by lessening workloads, currently wearing HMDs cause drivers to
become overconfident by following lead cars closer while increasing their reaction time.
3. Introduction
Automotive distraction and accidents have been on the rise since 1995, when the
cellular telephone was introduced (Strayer & Johnston, 2001; Horrey, W. J., 2011; Caird
et al., 2008). Texting and driving, a new form of distraction did not receive much thought
until the mid 2000's when a majority of the population in the United States owned the
technology. Although distracted drivers cause only 30% of accidents, the amount of
people injured as a result of distracted driving is still very high. The Center for Disease
Control reported in 2015 that every day nine people are killed and 1,153 people are
injured in the United States alone due to distracted driving.
Effects of Cell Phone Use
It takes a few years for products to become accepted, financially and socially. In
the nine years between 1999 and 2008 the percentage of Americans who owned a cell
phone rose from 33% to 91% (Wilson & Stimpson, 2010). It is important to understand
the impacts these recent technological advancements have on distraction and driver
performance.
Whereas 91% of Americans own cell phones, only 65% own smart phones (PRC,
2015). According to Dr. Michio Kaku, each smart phone has more computing power
than all of NASA in 1969, when it placed two astronauts on the moon (Kaku, 2011). The
modern day smart phone has all of the capabilities of many computers: GPS, Internet
Access, applications, text-based messaging, and voice-communication. Although few
people use game-based applications, such as 'Angry Birds' or ‘Fruit Ninja', while
operating vehicles social-media based applications are more common.
4. Texting while driving is considered the leading cause of automotive distraction.
Not only does the activity take time and attention away from the road, but often the user
is unable to accurately recognize their own driving errors (Watson & Strayer, 2010). This
makes drivers more likely to become overconfident in their ability to drive while
distracted (Peters & Peters, 2001).
It is widely accepted that texting while driving reduces attention to the road,
which may lead to near misses or accidents (Caird et al., 2008). As cell phones and
texting became common in the US, accidents and near miss collisions increased
(Wilson & Stimpson, 2010). As of this writing, 41 states in the US, as well as many
countries, have started campaigns to end texting and driving. These campaigns include,
giving tickets for texting while driving. Some states began having catchy slogans or
sayings to stop tempted people from texting while driving, Arizona is one such state with
road signs saying "Texting and Driving leads to the Dark side".
Surprisingly, Colorado is the only state to place any regulation on hands free
voice texting devices. Moreover this law only affects drivers under the age of 18. With
new technology coming out every year people are exposed to more and more
distractions, splitting the driver’s attention between the road and the technology. It would
be useful, however, to determine if using a head mounted display (HMD), like Google
Glass, would be safer alternative to texting and driving.
The Effect of Voice Texting
Voice texting has become widely accepted as a better alternative to physical
texting on a smart phone; to the point that voice texting and voice activated commands
have been implemented in many cars from economy cars to luxury brands. However it
5. is unclear whether voice activated applications and voice texting help the user perform
better in the event of an incident on the road. Research on this alternative way of
texting, suggesting that there is no difference voice texting and physical texting through
a smart phone (Stayer & Johnston, 2001; Carid et al., 2008).
Although voice texting is new, many researchers agree that voice texting still
significantly impairs a user’s ability to operate a vehicle (Stayer & Johnson, 2001; Caird
et al., 2008; He, Chaparro, Nguyen, Burge, Crandall et al. 2014). One Problem with
voice texting is that, although the driver can look at the road they are susceptible to
inattentional blindness. Despite these problems, automotive manufacturers continue to
add more voice-text and Bluetooth applications to satisfy public demand.
What is Google Glass?
Google Glass, created in 2012 and recently known only as Glass, is one of the
most newsworthy technological advancements in the past couple decades. Designed
for a high paced lifestyle, Google Glass has the ability to replace everything from eye
wear to a person’s smartphone. As technologies like Google Glass become more
common, it is likely that people will begin to use them while driving. Functions, such as
fatigue gauges and voice text, being added to Glass might improve driving safety.Glass
is a HMD that uses a clear cube that, when stationed properly, sits thirty degrees above
the normal field of vision over a single eye. When a user views the screen it is
comparable to that of a twenty-five inch television, eight feet away, in the upper right
hand corner of the user’s field of vision (see Google Glass Help, Tech Specs). The cube
is clear when the device is off, but when it is turned on the image projected onto the
cube covers a portion of the user’s field of vision. Google Glass has the ability to access
6. information ("pair up") from a user’s smart phone and project it onto the HMD accessing
photographs, text messages and even event dates.
Like the smart phone, Google Glass has its own application store from which
users can download games and social media applications. Google Glass has the
capability to perform many of the tasks that once required a smart phone. Making phone
calls and voice activated texting are some of the most commonly used applications for
Glass users; however users also have access to GPS on a device where they can
maintain their eyes in the general direction they are moving. In addition to a forward
facing camera social media, such as Instagram or SnapChat, is now a more viable
option for the user operating a vehicle.
Google Glass as a Safe Alternative to Texting on a Smartphone
It is fairly easy to see why many individuals would assume that Google Glass is a
safer alternative to texting when operating a vehicle. It provides the hands free features
7. that many luxury cars provide and allows you to keep your eyes on the road when
texting or using social media. Unfortunately, although the driver is looking at the road
their full attention is not dedicated to driving, and they have a chance of falling subject to
inattentional blindness (Strayer, Drews & Johnson, 2003). Specifically, although the
driver’s eyes are focused on the road, their attention may be focused on the screen.
The voice texting function provided by Glass may give drivers a false sense of
(Sawyer, Finomore, Calvo, Hancock 2014). Voice text is operated by a quick up and
down motion of the head to turn on the device, followed by the user saying "Okay Glass,
Respond to text" then the user says the message they wish to send. Glass uses
Google's voice activated software, which shows the text for the user to approve or deny
before the message is sent. Many argue that because the voice text function allows
users to keep both hands on the wheel and maintain constant view of the road, rather
than continuously looking down at the smart phone screen, this too would allow the user
to become faster in response to possible incidents in the road. However past research
shows that speech-based text entry still significantly impairs the user’s ability to drive
(He, Chaparro, Nguyen, Burge, Crandall et al. 2014; Rumschlag, Palumbo, Martin,
Head, George et al. 2015; Issar, Kadakia, Tsahakis, Yoneda, Sethi et al. 2013).
In fact all of the applications that are supposed to make driving safer, such as
voice texting and a heads up displays, have been inefficient and cause similar levels of
distraction as texting and driving (Strayer & Johnson, 2001; Caird et al. 2008; Sawyer,
Finomore, Calvo & Hancock, 2014).
8. Studies examining voice texting while driving demonstrate that users follow cars
closer and have a harder time staying within the lanes. There is no difference in
preventing distraction compared to texting on a physical device and significantly worse
than their control group counterparts (Stayer & Johnson, 2001; Caird et al., 2008;
Owens, McLaughlin, & Sudweeks 2011).
In the few studies where Google Glass is tested researchers compared texting
while driving, voice activated texting through Google Glass, and the effects that Google
Glass has when being worn (Sawyer, Finomore, Calvo & Hancock, 2014).
Conclusion
Despite the growing prevalence of wearable technology, there is still little
research on the effects HMDs on driving. Although Google Glass has only recently
become available and is operated by fewer than 300,000, according to CIO (Sacco,
2014), it is expected to grow exponentially after the initial release of the full product.
Should HMDs follow the same growth trend as cell phones, it is important to understand
the impact that using one of these devices has on a user’s ability to operate vehicles
safely.
It is hypothesized that similar to driver using a smartphone, drivers using Glass to
voice text will show increased brake reaction time and decreased ability to stay in their
lane. Indeed there should be no difference in reaction time or lane keeping between
these two conditions. Further, simply wearing a pair of Google Glass, without power, will
cause some level of distraction, thus increasing the driver’s reaction times.
Methods
Participants:
9. Fifteen college-age participants (11 men and 4 women, M= 20.733 years of age,
SD= 1.033 years of age) from Arizona State University volunteered to participate in this
driving simulation. All participants were 18 years of age or older with a valid drivers
license (M= 3.6 years, SD= 1.595 years). To reduce the amount of training, all
participants were required to own their own smart phone and understand how to use the
text messaging system from the device. To ensure that the participant would be able to
accurately see the simulator screens while operating the Google Glass, all participants
were required to either have corrective contact lenses or not require any corrective
lenses.
Experiment Set-Up:
The DS-600c Advanced Research Simulator by DriveSafety was used. The
simulator was comprised of 3 LCD televisions, providing a 300-degree wraparound
display; a full-width automobile cab; and a motion platform. Tactile and proprioceptive
feedback cues were provided via dynamic torque feedback from the steering wheel and
vibration transducers mounted under the driver’s seat. The motion platform provided
coordinated inertial cues for the onset of longitudinal acceleration and deceleration. The
data-recording rate was 60 Hz.
Procedure:
The car following task was identical to that used in several previous studies
(e.g., Scott & Gray, 2008; Mohebbi, Gray & Tan 2010; Gray 2011, McNabb & Gray
Under review). Drivers followed a lead car, on a two-lane road and were instructed to
stay in their own lane and to pass the lead car only when it came to a complete stop.
Drivers were given a 4-minute practice drive in order to become adjusted to the
10. simulation, as well as define a baseline. During the simulation, drivers were instructed to
maintain constant time headway (TH) of 2.0 sec with the lead car. When drivers had a
TH greater than 2.0 sec the words “Speed Up!” would appear on the display, however
they were free to maintain any TH below 2.0 sec.
The lead car was programmed to travel at speeds ranging between 55 and 65
mph, with an average of 60 mph. Since the lead car was changed speeds at, seemingly
random, preprogrammed intervals making it difficult to follow. In order to be directly
comparable to previous studies, the brake lights of the lead car were disabled (Ho,
Reed & Spence, 2007; Scott & Gray, 2008; McNabb & Gray, Under Review). Should the
participant come in contact with the lead car, an audio recording of a crash would play
and the lead car would disappear from view. There was no tactile response if the
participant came in contact with the lead car.
This study consisted of four different tasks, three potentially distracting conditions
and the baseline condition. The full track that was used for each condition contained 10
full stops of the lead car, which took the participants between 6 and 7 minutes to
complete. In order to directly comparable to previous studies, each participant
performed the baseline condition first. Between each condition the participants were
offered time to rest to reduce the chance of motion sickness and given a NASA-TLX
form to fill out in order to determine the work load the participant experienced during the
simulation.
Before starting the experiment, each participant was shown two separate one
minute training videos explaining how to operate Google Glass's voice activated text
messaging system. One training video explained how to turn on Google Glass and send
11. a text message. The second video explained how to receive and have Google Glass
read a message to you. In between each video the participant was given three minutes
to practice and understand what they just learned in the training video.
While operating in any of the condition that involved operating Google Glass,
participants were instructed to keep their head level so Google Glass would stay at the
designed thirty degrees above normal line of vision. When the participant attempted to
tilt their head forward in order to overlay the HMD with the simulator the simulation was
either restarted or the data was thrown out. Other than task specific details, the
participants received the same instructions throughout the entire experiment. The
participant were instructed to follow the car in front of them throughout the country at a
safe distance and were not informed of any sort of speed limit.
Wear-Only Task. In this task participants were asked to simply wear Google
Glass and drive around the simulator track. This task was meant to show if there was
any connection with wearing the Google Glass device and any sort of distraction a user
might experience. Participants were instructed not to operate the Google Glass in the
duration of the condition.
Texting with Google Glass. In this task participants were asked to use Google
Glass to text with the experimenter while driving around the simulator track. This task
was meant to understand whether or not using Google Glass's HMD, and voice texting,
is actually a safer alternative to texting with a Smart Phone. During the condition the
participant was asked a series of short math problems and has to respond to them
using the voice texting function of Google Glass.
12. Texting with Smart Phone. In this task participants were asked to use their own
smart phone to text with the experimenter while driving around the simulator track. This
task was meant to understand how much texting with a smart phone affects the
participant’s ability to operate a vehicle accurately. During the condition the participant
was asked a series of short math problems and has to respond to them using their
Android phone.
Data Analysis
Brake reaction time (BRT) and time headway (TH) were used as the two
dependent variables in order to assess driving performance, since in previous studies
they have been shown to be an indicator of user distraction. The data was analyzed
through a within-subjects MANOVA assessing the interaction of two different variables,
the type of distraction (Google Glass or Smart Phone) and the conditions the
participants are under (multitasking or driving without distraction). A one-way ANOVA
was used to analyze the NASA-TLX forms that were administered after each condition.
For all of the results the statistical significance was set at p<0.05. The effect size was
calculated using partial eta squared for all ANOVAs.
Results
The mean BRT across the four conditions is shown in figure 1. The within-
subjects MANOVA performed on the data collected indicates a significant effect Wilk’s
lambda=0.039, F(4,60)=4.837, p=.000, = .961. The first comparison indicated that
the condition Glass Text (Mean=1.28s) had a higher BRT than the Texting (Mean=0.99s)
condition with moderate significance p=0.059. The second comparison revealed that the
ηρ
2
13. BRT for the baseline (Mean=0.87s) and the Wear Only (Mean=0.97s) condition was not
significantly different. Finally, post-hoc tests were used to compare the BRT in each of
the conditions to the Baseline these tests revealed that only the Glass Text condition
significantly increased the reaction time of the user, p=0.004.
The mean TH variability across the four conditions is shown in figure 2. The
within-subjects MANOVA reveals no significant effect between the conditions
F(4,60)=2.344, p=.083, = .112.
Discussion
With todays world moving towards hands-free technology that is able to keep up
with our high paced lifestyles, it would not be unlikely to see such devices in the
automotive setting. Drivers use their cell phones to communicate with other individuals
and although voice texting should make driving safer much of the research supports
otherwise (He, Chaparro, Nguyen, Burge, Crandall et al. 2014; Rumschlag, Palumbo,
Martin, Head, George et al. 2015; Issar, Kadakia, Tsahakis, Yoneda, Sethi et al. 2013).
The purpose of the simulation is to create a worst-case scenario for a multi-tasking user,
a sudden dangerous situation while they are distracted. The two factors that we were
interested in was the type of distraction (Google Glass vs Smartphone) and the
condition of the participant (Distracted vs Driving without Distraction).
Although smartphone use has been recognized as a cause for user distraction,
many individuals have switched to hands free voice texting through their phone or car
which have little effect on creating a safer driving experience (Stayer & Johnston, 2001;
Carid et al., 2008). Since the integration of voice texting has little effect on a users our
ηρ
2
14. first hypothesis was that Google Glass would not significantly improve a users ability to
detect possible hazardous situations in the road, instead it would be very similar to the
effects of texting and driving on user performance where both would show significantly
worse BRT than driving without distraction. For our hypothesis to be true the BRT and
TH would be very similar but significantly worse when compared to the baseline
condition, however this hypothesis was not supported by the data collected for two
reasons. First, from the data collected the Glass Text condition was the only condition to
show significant results, although none of the TH revealed any significant effects.
Second, although Glass did not increase the users reaction time significantly compared
with the smartphone (p=.059), the texting and driving had a closer comparison to the
Wear Only condition than with the Glass Text condition.
Many companies have attempted to make devices that reduce the amount of
distraction that can occur through different applications however many of them still
cause users to become distracted. (Strayer & Johnson, 2001; Caird et al. 2008; Sawyer,
Finomore, Calvo & Hancock, 2014) Our second hypothesis was that simply wearing the
Glass would cause some level of distraction to occur, however still better than texting or
using the Glass. The data collected supported this hypothesis; simply wearing the
Glass, when powered off, created the similar levels of distraction that texting off of a
smartphone created. The level to which simply wearing the Glass would affect the
average BRT wasn't expected; the Wear Only condition was only one millisecond faster
than someone who was texting. Although neither the Wear Only nor the Text condition
performed significantly better than the Baseline condition, the effects of texting and
driving have been well documented and from the data it can be interpreted that simply
15. wearing Glass will cause the same effects. This was contrary to previous research
where the data showed a powered-off Glass causing as much distraction as someone
using a smartphone.
Given that Google Glass was created in 2012, and is still more or less
unavailable to the general public, it is unlikely that the participants in the experiment
have had previous experience with Glass. Although each participant was presented with
two two-minute training videos on how to operate the device, to the point of making it
through the texting process with little error, their level of proficiency was nowhere near
their level of expertise that they hold with their personal smartphone. Previous research
in the application of Google Glass in automotive settings found that giving a new user
five minutes of training produced the best results since the benefits of training after five
minutes plateaus (Sawyer, Finomore, Calvo, Hancock 2014).
The evaluation of Glass in an automotive setting goes beyond simply using the
voice-messaging system. Since Glass uses an open-source app development, new
applications are coming out on a daily basis, from social media to interactive games.
Many of these applications have not been empirically evaluated to fully understand their
impact on users driving ability and their reaction time.
The present findings suggest that operating a vehicle while using an HMD to
communicate "hands-free" is a worse alternative to texting and driving. The combination
of a closer, yet not significant, TH with the moderately significant increase in BRT
creates the conditions in which accidents may occur. At present, Google Glass creates
an unsafe environment in which users are lulled into a false sense of security, leaving
them open to inattentional blindness (Sawyer, Finomore, Calvo, Hancock 2014). With
16. the lack of an expert population to analyze further research into what applications cause
the user-distraction a systematic analysis of Glass applications would be needed in
order to properly asses which function is the root cause of the distraction.
19. References
Caird, J. K., Willness, C. R., Steel, P., & Scialfa, C. (2008). A meta-analysis of the
effects of cell phones on driver performance. Accident Analysis &
Prevention, 40(4), 1282-1293.
Gray, R. (2011). Looming auditory collision warnings for driving. Human Factors: The
of the Human Factors and Ergonomics Society, 53(1), 63-74.
He, J., Chaparro, A., Nguyen, B., Burge, R., Crandall, J., Chaparro, B., Cao, S. (2014).
Texting while driving: Is speech-based text entry less risky than handheld text
entry? Accident Analysis & Prevention, 72, 287-295.
Horrey, W. J. (2011). Assessing the Effects of In-Vehicle Tasks on Driving Performance.
Ergonomics in Design: The Quarterly of Human Factors Applications, 19(4), 4-7.
Issar, N. M., Kadakia, R. J., Tsahakis, J. M., Yoneda, Z. T., Sethi, M. K., Mir, H. R.,
Jahangir, A. A. (2013). The link between texting and motor vehicle collision
frequency in the orthopaedic trauma population. Journal of Injury and Violence
Research J Inj Violence Res, 5(2), 40-50.
Kaku, M. (2011). Physics of the future: How science will shape human destiny and our
daily lives by the year 2100. New York: Doubleday.
McGee, M. (2013, December 04). Google Posts 6 More Glass Training Videos - Glass
Almanac. Retrieved from http://glassalmanac.com/google-posts-6-glass-training
-videos/1731/
McNabb, J., & Gray, R. (Under Review). Staying Connected on the Road: A
Comparison of Different Types of Smart Phone Use in a Driving Simulator
Mohebbi, R., Gray, R., & Tan, H. Z. (2009). Driver reaction time to tactile and auditory
rear-end collision warnings while talking on a cell phone. Human Factors: The
Journal of the Human Factors and Ergonomics Society, 51(1), 102-110.
Owens, J. M., Mclaughlin, S. B., & Sudweeks, J. (2011). Driver performance while text
messaging using handheld and in-vehicle systems. Accident Analysis &
Prevention, 43(3), 939-947.
Peters, G. A., & Peters, B. J. (2001). The distracted driver. The journal of the Royal
Society the Promotion of Health, 121(1), 23-28.
20. Pew Research http://www.pewinternet.org/fact-sheets/mobile-technology-fact-sheet/
Rumschlag, G., Palumbo, T., Martin, A., Head, D., George, R., & Commissaris, R. L.
(2015). The effects of texting on driving performance in a driving simulator: The
influence of driver age. Accident Analysis & Prevention, 74, 145-149.
Sacco, A. (2014, July 4). How Many People Actually Own Google Glass? Retrieved
From http://www.cio.com/article/2369965/consumer-technology/how-many-
people-actually-own-google-glass-.html
Sawyer, B. D., Finomore, V. S., Calvo, A. A., & Hancock, P. A. (2014). Google Glass: A
Driver Distraction Cause or Cure? Human Factors: The Journal of the Human
Factors and Ergonomics Society, 56(7), 1307-1321.
Scott, J. J., & Gray, R. (2008). A comparison of tactile, visual, and auditory warnings for
rear-end collision prevention in simulated driving. Human Factors: The Journal of
the Human Factors and Ergonomics Society, 50(2), 264-275.
Strayer, D. L., Drews, F. A., & Johnston, W. A. (2003). Cell phone-induced failures of
visual attention during simulated driving. Journal of experimental psychology:
Applied, 9(1), 23.
Strayer, D. L., & Johnston, W. A. (2001). Driven to distraction: Dual-task studies of
simulated driving and conversing on a cellular telephone. Psychological
science, 12(6), 462-466.
Watson, J. M., & Strayer, D. L. (2010). Supertaskers: Profiles in extraordinary
multitasking ability. Psychonomic Bulletin & Review, 17(4), 479-485.
West, A. (2011, December 11). Cell Phone Driving Bans, State by State: Where You
Break the Law. Retrieved from http://www.pcworldcom/article/246574/cell_phone
_driving_bans_state_by_state_where_you_break_the_law.html?page=2
