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© Transport Research Laboratory 2011

Transport Research Laboratory Creating the future of transport

DRAFT PROJECT REPORT RPN2005

Smartphone use while driving

A simulator study

D. Basacik, N. Reed and R. Robbins

Prepared for: IAM (the Institute of Advanced Motorists)

Project Ref: 11111660

Quality approved:

Dan Basacik

(Project Manager)

Nick Reed

(Technical Referee)

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Disclaimer

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with IAM. Any views expressed in this report are not necessarily those of IAM.

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every effort has been made to ensure that the matter presented in this report is

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or omission, or reliance on part or all of the content in another context.

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Contents amendment record

This report has been amended and issued as follows:

Version Date Description Editor Technical Referee

1.0 23/11/2011 First full draft DB NR

2.0 09/12/2011 Second draft – IAM comments addressed DB NR



Contents

1 Introduction 2

2 Literature review 3

2.1 Why worry about distracted driving? 3

2.2 Does mobile phone use while driving increase accident risk? 3

2.3 How does using a mobile phone affect driving? 3

2.4 What is known about smartphone use or social networking while

driving? 4

2.5 Research hypotheses 5

3 Method 6

3.1 Participants 6

3.2 Equipment 6

3.3 Familiarisation 7

3.4 Study design 7

3.5 Participant instructions 7

3.6 Route design 8

3.7 Smartphone task 10

3.8 Overall design 14

3.9 Trial procedure 15

3.10 Recorded simulator data 15

3.11 Visual behaviour 16

3.12 Questionnaire 16

3.13 Calculation 16

4 Results 17

4.1 Participants 17

4.2 Reaction time (RT) tasks 17

4.3 Analyses of driving performance while using a smartphone 18

4.4 Visual behaviour 23

4.5 Effects of driving on smartphone use 26

4.6 Subjective effects of smartphone use on driving performance 27

4.7 Patterns of mobile phone use 29

4.8 Perceptions of legality 33

4.9 Perceptions of relative risks of driving behaviours 35

5 Discussion 36

5.1 Comparison with previous studies 37

Smartphoning while driving

Version 2.0 1 RPN2005

Executive Summary

A substantial body of research has shown that use of a mobile phone while driving leads

to poorer driving performance. Previous research has covered different elements of

telephone use, including hand-held and hands-free use while making a call and the

reading and writing of text messages.

Mobile phones have recently undergone a substantial change and ‘smartphones’ have

gained popularity. These devices allow users to take part in a much broader range of

activities than traditional mobile phones, including browsing the web, emailing, social

networking, and browsing and playing personal media. With ‘smartphones’ now

becoming common in the commercial marketplace, more and more drivers are able to

engage in a broad range of possible activities on their phone. There is a clear potential

for motorists to be tempted to conduct these activities whilst driving a vehicle.

This study set out to investigate whether there was an effect of social networking using a

smartphone on driving performance. Twenty-eight young male and female participants

took part in the study and drove a driving simulator through the same test scenario

twice: once while using a smartphone to interact with a social networking site, and once

without this distraction. This experimental approach allowed potentially hazardous road

situations to be designed and experienced twice, in complete safety.

The results of the experiment clearly show that participants’ driving performance was

impaired by the concurrent smartphone task, and the smartphone task was also affected

by driving. When compared with their driving performance without a smartphone:

Participants were more likely to miss the reaction time stimuli while using their

phone.

When they did respond, reaction times to visual and auditory stimuli were found

to increase by approximately 30% when using a smartphone to send and receive

messages on a social networking site.

They were unable to maintain a central lane position and this resulted in an

increased number of unintentional lane departures.

They were unable to respond as quickly to a lead vehicle gradually changing

speed, thus driving at a more variable time headway.

They spent between 40% and 60% of the time looking down while using a

smartphone to write or read messages, compared with about 10% of the time

looking down in the same sections of the control drive.

These results suggest that participants’ driving was impaired when they were using a

smartphone to send and receive messages on a social networking site. The results of this

study indicate that this reduction in driving performance is likely to have been a result of

three different types of distraction: having to concentrate on the smartphone task

(cognitive), holding the phone (physical), and the significant increase in time spent

looking at the phone (visual) in order to interact with it. Although participants did reduce

their speed, this was not enough to compensate for the poorer driving performance;

even though they were driving more slowly, they were still unable to control the vehicle

as well as they did when they were not using their smartphone.



1 Introduction

There is a substantial body of research that has shown the potential distraction posed to

a driver by the use of a mobile phone. This research has covered different elements of

telephone use, including hand-held and hands-free use while making a call (Burns et al.,

2002, Strayer et al., 2006, Parkes et al., 2007) and the reading and writing of text

messages (Reed and Robbins, 2008).

In recent years, however, mobile phones have undergone a substantial change and so-

called ‘smartphones’ have gained popularity. Aside from making phone calls and sending

text messages, these devices enable users to send and receive emails, connect to the

internet to browse web pages, browse and play music and videos, social network and

carry out a broad range of other activities. According to Ofcom, smartphone sales

accounted for 48% of all mobile phone sales in the UK in the first quarter of 2011

(Ofcom, 2011). With ‘smartphones’ now becoming common in the commercial

marketplace, more and more drivers are now able to engage in a broad range of possible

activities on their phone. There is a clear potential for motorists to be tempted to

conduct these activities whilst driving a vehicle.

Furthermore, even for the more traditional calling and texting functions of a phone,

smartphone interfaces are significantly different to mobile phone interfaces from five to

ten years ago. For example, many smartphones have touchscreens rather than keypads

(Canalys, 2010), and with increasing functionality come the issues of device and menu

complexity. Such interface issues are likely to change how people use the device and

therefore how distracting it is to use the device while driving.

From the findings of research looking at more traditional aspects of mobile phone use in

a vehicle, it is likely that smartphone use in a vehicle would pose a distraction and lead

to a detriment in driving performance. What is not clear is the extent to which

performance would be expected to decrease.

This report describes a study that has investigated the effects of using a smartphone for

social networking while driving using a high-fidelity driving simulator. Chapter 2 presents

a review of the literature on the use of mobile phones while driving and gives some

background to the study, whilst Chapters 3 through 5 present the method, results and

findings of the driving simulator study.



2 Literature review

2.1 Why worry about distracted driving?

In recent decades driver distraction has been a popular research topic and continues to

receive significant attention. Two main factors are likely to be driving ongoing research.

Firstly on-road studies are showing just how salient a factor distraction is in crashes. In

NHTSA’s 100-Car Naturalistic Driving Study, participants were given an instrumented

vehicle to drive instead of their own vehicle. The resulting dataset included 43,000 hours

of driving (approximately 2 million vehicle miles) and showed that engagement in a

secondary task contributed to more than 22% of all crashes and near-crashes that were

recorded in the study period (Klauer et al., 2006).

The second reason is that the potential for drivers to be distracted is increasing as

technology develops. More recent sources of distraction outside of the vehicle include

motion picture advertising billboards (Chattington et al., 2010), while smart phones and

systems built into the vehicle give the driver the opportunity to engage with email, social

networking sites, music collections and to conduct a range of other activities.

Thus, an improved understanding of distraction as a contributory factor to crashes, and

an awareness of the increasing potential for drivers to be distracted by technology are

driving research efforts in this area.

2.2 Does mobile phone use while driving increase accident risk?

Data from the 100-car study (Klauer et al., 2006) shows that distraction is associated

with accidents but does not distinguish between different distractors.

An earlier study examining the mobile telephone records belonging to 699 drivers

involved in car accidents (with property damage only) showed that the risk of collision

increased fourfold with mobile phone use (Redelmeier and Tibshirani, 1997). Relative

risk of collision was 1.3 times higher if calls were made up to 15 minutes before the

collision and this figure rose to 4.8 times higher if a call was placed within 5 minutes of

the collision (Redelmeier and Tibshirani, 1997). Interestingly this study found no

difference in accident risk between those having hand-held and hands-free mobile phone

conversations, suggesting that the risk of collision isn’t related to holding the phone.

The results of this study indicate that having a mobile phone conversation while driving

increases crash risk.

2.3 How does using a mobile phone affect driving?

Studies conducted on-road or in laboratory settings have looked closely at the particular

effects that mobile phone use has on the performance of activities required for driving.

They have concluded that mobile phone use is associated with:

Increased ratings of mental workload (Parkes et al., 2007; Lesch & Hancock,

2004; Harbluk et al., 2002; Burns et al., 2002; Parkes et al., 1993)

A reduction in people’s perceptual visual fields by up to 10% (Maples et al., 2008)

Longer glances ahead, at the expense of other monitoring behaviours such as

checking the mirrors and vehicle instruments (Parkes et al., 2007; Harbluk et al.,

2002)



Poorer awareness of and response to the traffic situation (Parkes et al., 2007,

Parkes and Hooijmeijer, 2000) despite longer glances ahead

Slower detection of and responses to hazards (Caird et al., 2008)

A reduction in speed in an attempt to compensate for the perceived impairment

caused by using a phone (Reed and Robbins, 2008; Burns et al., 2002)

This list shows how driving performance can suffer when people are given the additional

task of using a mobile phone.

Interestingly, driving simulator studies have also shown that for some performance

measures, hands-free mobile phone conversations can reduce driving performance as

much as hand-held mobile phone conversations. For example, Parkes et al. (2007)

concluded that mobile phone use delayed reaction times when compared with a control

condition, and also when compared with a condition in which participants were at the UK

legal limit for drink-driving, yet there was no statistically significant difference between

the hand-held and hands-free mobile phone conditions.

When taken together with the studies described in Section 2.2, a clear conclusion is that

having a mobile phone conversation while driving impairs driving performance.

2.4 What is known about smartphone use or social networking while driving?

This review has not found research looking at the effects of smartphone use for social

networking on driving. However, it is possible to make high-level predictions based on

studies which have looked at other devices or tasks that are in some ways similar.

Reading a message received through a social networking application on a smartphone

may be similar to reading a text message received on an ordinary mobile phone. Reed

and Robbins (2008) investigated the effects of reading and writing text messages on

driving performance. When reading a text message, participants took longer to respond

to stimuli, and were less able to keep to the centre of their lane or at a fixed distance

behind a lead vehicle. Similar findings are also reported by Cooper et al. (2011) who

studied driving performance while texting. Their experiment was carried out on a test

track and the authors report significantly slower responses, more missed response

events, reductions in speed, poor lane keeping and fewer glances ahead while texting.

Writing a message on a social networking site could be comparable with writing a text

message. The studies carried out by Reed and Robbins (2008) and Cooper et al. (2011)

found that writing a text message on a mobile phone had an even greater effect on

driving performance than reading a message. All of the participants used mobile phones

with ordinary push-button keypads in the former study, and although a wider variety of

phone interfaces were used in the latter, no analysis of these differences is presented.

Owens et al. (2010) examined driving performance while text messaging using handheld

and in-vehicle systems. Participants used either a phone with a standard keypad or a

touch screen but differences between groups were not reported.

Johnson (2011) highlights perceptual issues which affect how efficiently people can use

touchscreens for data entry. He argues that while it is possible for people to learn to

touch type without looking at a keyboard, the smooth surfaces of touch screens prevent

people from being able to feel the location of keys, and therefore interactions require

visual input. Sears (1991) found that participants in his study were able to type on



average 58 words per minute on a standard keyboard, but only 25 words per minute on

a touchscreen keyboard with the same layout.

Keyboard and key size have a significant effect on typing speed. An experiment by Sears

et al. (1993) has shown that both novice and experienced participants were able to type

more quickly on a larger touchscreen keyboard with larger keys, than a smaller keyboard

with smaller keys. The keyboards used in this study ranged from 6.8 to 24.6cm wide.

Tsimhoni et al. (2002) gave participants of their study the task of entering an address

into a satellite navigation system while driving. Participants used three methods to enter

the address; two of these used speech recognition and one used a touch screen

keyboard on a 7 inch screen (this, compared with the 3.5 inch screen on the iPhone 4,

not all of which is taken up by a keyboard). Keys were 12.7mm high by 12mm wide, and

spaced 0.7mm apart. The study showed that the speech recognition systems were

clearly favourable; people were able to complete address entry much more quickly and

were able to keep closer to the centre of their lane, suggesting that manual text entry on

the touch screen was a distracting task.

In summary, the literature seems to suggest that reading text on a mobile phone leads

to poorer driving performance. One would expect this to hold true when using a

smartphone for social networking. There is also evidence to suggest that text entry on a

mobile phone distracts from the driving task. Furthermore, there are suggestions that

use of touch screens for text entry brings with it issues that could exacerbate the

problem.

2.5 Research hypotheses

Based on this literature it is possible to come up with some predictions about driving

performance while using a smartphone for social networking. These predictions form the

research hypotheses to be investigated during the driving simulator study:

Participants will drive more slowly when they are using a smartphone

Participants’ reaction times will be slower when using a smartphone

Participants’ lane position will vary more while using a smartphone

Participants will spend more time looking inside the vehicle while using a

smartphone

Participants will report that their driving was worse while using a smartphone

The method used during this study is described in Chapter 3. It is based heavily on that

used by Reed and Robbins (2008), which itself is based Burns et al. (2002), enabling

comparison of the extent of driver impairment with previous studies.



3 Method

3.1 Participants

Twenty-eight participants were recruited from the TRL participant database to take part

in the study, with an approximately even split between males and females. They met

the following criteria in order to be included in the study:

Participants described themselves as regular users of Facebook on smartphones

Participants had the Facebook app on their smartphone

Participants were current owners of a touchscreen smartphone (iPhone or

Android)

Participants were aged between 18 and 25

Participants drove more than 5000 miles per year

Participants had experience of driving on a motorway

Participants had driven the simulator before

Participants successfully completed a familiarisation drive in the simulator

Participants were required to use their own phones for the study.

3.2 Equipment

The TRL Driving Simulator (DigiCar) consists of a medium sized family hatchback (Honda

Civic) surrounded by four 3 × 4 metre projection screens giving 210º front vision and

60º rear vision, enabling the normal use of the vehicle’s driving and wing mirrors. The

road images are generated by four PCs running SCANeR II software (manufactured by

Oktal) and are projected onto the screens by five Digital Light Processing (DLP)

projectors. Images are refreshed at a rate of 60Hz (every 16.7msec) whilst data is

sampled at a rate of 20Hz (every 50msec).

Figure 1: TRL driving simulator, DigiCar



Electric motors supply motion with 3 degrees of freedom (heave, pitch and roll) whilst

engine noise, external road noise, and the sounds of passing traffic are provided by a

stereo sound system.

Two studies have demonstrated the validity of the TRL simulator (Duncan, 1995; Sexton,

1997) and Diels et al. (in press) confirm that the current simulator system is at least as

accurate as that used in the Duncan and Sexton studies.

3.3 Familiarisation

Participants were required to complete a ten minute familiarisation drive on a benign

motorway environment prior to completing any of the test drives. This was to help

participants to become comfortable with controlling the simulator vehicle and driving in

the virtual environment. The drive included a car following task in which participants

were required to drive at a safe and constant distance behind a lead vehicle. During this

task, white chevrons were included on the motorway (as used on some sections of UK

motorways) helping the participant to judge a safe distance to the lead vehicle.

3.4 Study design

After familiarisation, participants carried out two drives:

A smartphone drive in which they had to read and write messages and update

their status using a social networking application

A control drive along the same route, but without having to use a smartphone

To counterbalance any learning effects caused by driving the same route twice, the order

of these two drives was alternated between participants.

3.5 Participant instructions

Participants were given the following instructions:



Before the smartphone drive, participants were also instructed:

If participants asked whether they should put their phone in a specific place in the

vehicle, they were advised that they should keep it wherever they normally would while

they were driving.

3.6 Route design

The simulator route driven by participants consisted of four sections with smooth

naturalistic transitions between each section. These are shown in Table 1.

During this drive you will be asked to send and receive private messages on

Facebook and update your Facebook status. Your contact for all of the private

messages is Daniel Boyd, who we added as your Facebook friend earlier. Please only

send and read messages when you are asked to. Please write messages as you

normally would, ie using short words and predictive text.

Please adjust the seat position and secure the safety belt. The car controls work

in the same manner as any normal car and it operates with a manual gearbox.

You need to make sure the car is in neutral when you start it and it needs plenty

of revs, otherwise it has a tendency to stall.

It is important that you drive as you would normally. We don’t want you to drive

as if you are on a driving test nor as if the simulation is a computer game. We are

not here to judge your driving, so please do not feel anxious.

A red bar like the one you can see on the screen now will appear during your

drive. There is also a buzzing noise that will sound during the drive. When you

hear the buzzing noise, or see the red bar please press the clutch pedal as quickly

as you possibly can. You will hear the buzzing sound about 20 seconds into this

drive as a practice to help you recognise it.

The drive will start on the motorway with normal traffic. After a while, the

motorway will end and you will reach a series of bends. You should try to keep to

40 mph through this section and the simulator will assess your ability to keep to

the centre of your lane through the bends.

After the series of bends, you will drive on the motorway again. After a period of

time you will see a vehicle in front of you. Please pull up behind this vehicle and

follow it, doing your best to keep at a safe and constant distance behind it. A

voice instruction will let you know when the car following task has finished.

There will be voice instructions to remind you about these tasks.



Table 1: The road sections used for the simulator trial

Section Description Length Configuration

1 Motorway 1 17.5 miles 3 lane motorway plus hard shoulder in each

direction. Light traffic present

2 Two loops 4.6miles

Each loop is a two-lane ‘figure 8’ with a long left

turn and long right turn separated by a short

straight

3 Car following 8.1 miles

3 lane motorway plus hard shoulder in each

direction. One vehicle present that the participant

is required to follow at a steady distance

4 Motorway 2 7.3 miles 3 lane motorway plus hard shoulder in each

direction. Light traffic present

Total 37.5 miles

In the loops section, participants were instructed to try to stay in the centre of their lane

and to drive at 40mph.

In the car following section, participants were instructed to follow the lead vehicle at safe

and constant distance (as they would have experienced in the familiarisation drive). The

lead vehicle smoothly and repetitively increased and decreased its speed between

43.8mph (70kph) and 68.8mph (110kph) over a period of 20 seconds.

3.6.1 Reaction time events

During both the smartphone and control drives, participants were required to respond to

trigger stimuli on four occasions in order to test their reaction times. In three of the

reaction events, the trigger stimulus was a short auditory tone (60dB; 0.45 seconds

duration; 333Hz). The fourth reaction time trigger event was the presentation of a red

bar stimulus above the carriageway and ahead of the driven vehicle across all motorway

lanes. This is shown in Figure 2.



Figure 2: Red bar stimulus

Participants were instructed to respond by depressing the clutch pedal as quickly as

possible. Clutch depression is measured from 0 (foot off clutch) to 1 (clutch fully

depressed). The threshold for clutch activation was 0.1 (10% clutch depression). If

clutch depression was greater than 10% at the time of the reaction time trigger, the

event would have been ignored but this did not occur in any of the trials. If participants

failed to respond within 10 seconds, this was treated as a missed event.

3.7 Smartphone task

The research brief was to use a social networking task. This would serve the purpose of

straying beyond the functionality of a standard mobile phone whilst still requiring

participants to take part in written communication, as one would when sending and

receiving text messages.

3.7.1 Choice of social networking application

A plethora of applications are available which allow users to access many websites via

their smartphones. For the current study, we conducted market research to identify a

widely used social networking application. This was to ensure the secondary task used in

the experiment was representative of real-world usage.

Table 2 shows which mobile applications were most widely visited by UK mobile

consumers in April 2011. The data show that nearly 8.8 million UK mobile owners used



an app that connected to the internet during April 2011, with Google Maps ranking as

the most accessed app with 6.4 million unique users. It can be seen that the social

networking application ‘Facebook’ was ranked as the third most often used application.

Other popular social networking applications such as ‘LinkedIn’ or ‘Twitter’ did not

feature in the top 10.

Table 2: Connected Mobile Applications Ranked by Unique Visitors (from

Comscore, 2011)

Rank Mobile app Total unique visitors

1 Google Maps 6,419,503

2 Yahoo! Weather 3,567,047

3 Facebook 3,456,442

4 Google Mobile 2,554,329

5 YouTube 2,438,348

6 eBay 1,195,496

7 Sky Sports Live Football Score Centre 1,004,085

8 Yahoo! Stocks 959,289

9 WhatsApp Messenger 798,656

10 Sky News 732,374

Total connected app users: 8,735,197

Figure 3 shows the demographics of Facebook users. It can be seen that for all age

categories, there tends to be approximately an equal split between male and female

users with slightly more female users. Furthermore, the figure shows that Facebook use

is biased towards the younger age categories. In the context of the current study, it is of

relevance to point out that motorists under 24 years of age are overrepresented in the

accident statistics (DfT, 2011). Hence, the issue of smartphone use by younger drivers is

of particular relevance.

On the basis of the above information, ‘Facebook’ was chosen as an appropriate

application to be used in the experimental study.

Figure 3: UK Facebook users split by age and gender (Sources: Facebook, Alexa,

June 2010)

Age (

years

)

Number of users



3.7.2 Choice of smartphone operating system

Table 3 shows the percentage of users for the different smartphone operating systems.

Apple and Google Android account for 96% of the market share. Because of the

similarity in both functionality and user interface of the Facebook application on both

Apple and Android, the experiment allowed participants to partake with either of the

operating systems (OS).

Table 3: Share (%) of Connected Application Users by Smartphone Operating

System (from Comscore, 2011)

Smartphone Operating System Total Unique Visitors % Share

Apple iOS 5,702,166 65%

Google Android OS 2,699,982 31%

Symbian OS 118,957 1%

Other OS 356,871 3%

Figure 4 shows the Facebook home page on the Apple (left) and Google Android (right)

operating systems. It can be seen that the application is similar on both OS whereby the

Apple OS provides slightly more functions (“Chats” “Groups” “Places”) on the Facebook

homepage. In selecting the tasks to be completed by participants during the study,

those related to these three functionalities were excluded.

Figure 4: Sample screenshot of the Facebook home page on Apple (left) and

Android (right) operating systems



3.7.3 Facebook tasks whilst driving

Through the course of the drive participants were required to perform a succession of

different tasks using the Facebook application. Participants were asked to become

Facebook ‘friends’ with a ‘Daniel Boyd’, whose account was used by experimenters to

send messages to participants and receive messages from them during the smartphone

drive.

3.7.3.1 Writing messages

Participants had to write five messages in the drive. All comprised an approximately

similar number of characters. The instructions as to what to write and the message

recipient were delivered as automated verbal messages in the simulation. Participants

were instructed to compose the text in their own usual style. This included using

predictive text, autocorrect and applying SMS language. The first message was included

as practice to ensure participants were comfortable what was required of them.

Table 4 shows the messages that participants were required to compose.

Table 4: Messages composed by participants whilst driving

Message Section Message Characters

Practice 1 I am driving a great car simulator 34

1 1 Happy birthday Have fun at the party 36

2 2 Nice to see you at the cafe yesterday 37

3 3 Dont worry Have a nice time in Paris 36

4 4 Sorry about your ankle Get well soon 36

3.7.3.2 Reading messages

Participants were sent two messages over the course of their drive. Participants were

informed by an automated voice instruction that they were about to receive a message

and that they would need to read the message in order to be able to answer the

questionnaire at the end of the drive. Table 5 shows the messages that participants

received.

Table 5: Messages received by participants whilst driving

Message Section Message

1 1 Edward has forgotten his BOWTIE for the wedding

2 2 Fiona won the SILVER medal in the 100m sprint

3.7.3.3 Updating Facebook status

In addition to writing and reading messages, participants were also asked to update their

Facebook status. Table 6 shows the section and text for the status update.



Table 6: Status update text

Section Text Characters

3 I am near the end of the virtual world 38

3.7.3.4 Control messages

To compare how quickly participants could write short messages on their smartphone,

participants were timed composing some comparable text on their smartphone when

they were not driving. These were as follows:

Table 7: Timed messages composed by participants without distraction (i.e.

driving)

Message Characters

Best of luck for your driving test today 40

Well done Looking forward to the wedding 40

Please can you bring red wine tonight 37

Where did you get those new trousers 36

3.8 Overall design

Figure 5 shows the incidence of social networking tasks and reaction time (RT) events in

the smartphone drive. Note that the control drive is exactly the same as the smartphone

drive with the exception that participants were not required to interact with their phone.

Figure 5: Schematic timeline of events in the drive



3.9 Trial procedure

The trial proceeded as shown in Table 8.

Table 8: Trial procedure and schedule

Time from start Activity Duration

0 Welcome and introduction 5

5 Control messages (either before or after drives) 5

10 Simulator: Familiarisation drive 10

20 Background questionnaire 10

30 Drive 1 (Smartphone or Control) 40

70 Break 10

80 Drive 2 (Control or Smartphone) 40

120 Phone usage questionnaire 20

140 Depart

3.10 Recorded simulator data

Table 9 shows the data recorded by the simulator. All data was recorded at 20Hz.

Table 9: Data recorded by the simulator

Data Notes

Time Time elapsed since the start of the trial

X position of interactive vehicle The X position of the interactive vehicle within the

map of the simulated environment.

Y position of interactive vehicle The Y position of the interactive vehicle within the


Z position of interactive vehicle The Z position of the interactive vehicle within the


Speed Current speed of the interactive vehicle

Distance through trial Distance travelled by participant relative to the start

of the virtual road

Lateral distance from centre of

road

The distance of the centre of the interactive vehicle

from the centre of the road

Headway The distance headway between the interactive vehicle

and the back of any vehicle ahead.

Time Headway The time headway between the interactive vehicle and

the back of any vehicle ahead.

Accelerator pedal Current proportion of accelerator pedal depression.

Brake pedal Current proportion of brake pedal depression.

Clutch pedal Current proportion of clutch pedal depression.

Steering wheel Current angle of steering wheel rotation



3.11 Visual behaviour

In addition to the simulator data, a video of participants’ faces was recorded during the

drive in order to analyse visual behaviour. Videos coding took place as follows.

The coders skipped to the points in each smartphone drive where the automated voice

instruction ended. From there, they watched the video at (at least) half speed, using a

stopwatch to record:

Total time spent looking down (this does not distinguish between looking at the

phone or other parts of the in-vehicle environment)

Total time spent looking up (ie at the road, mirrors, etc)

Duration of interaction with phone (sum of the above)

Smartphone interaction was assumed to finish if the participant looked ‘up’ for at least

five consecutive seconds.

The same locations of each participant’s control drive were also coded.

3.12 Questionnaire

A post-trial questionnaire was also administered in order to record participants’

perceptions of their riving performance and opinions about mobile phone use while

driving.

3.13 Calculation

Data processing was conducted using Microsoft Excel 2007 and statistical analysis took

place using SPSS 19.0. In all statistical tests p values of less than 0.05 were taken to be

significant. Where shown, error bars indicate the 95% confidence interval of the mean.



4 Results

4.1 Participants

Twenty-eight participants took part in the study. Twelve were female and sixteen were

male. Participants were aged between 18 and 26 years (M=22.4, SD = 2.32). Only

participants who used Apple or Android phones with touchscreen keypads and who

described themselves as being regular users of the Facebook application on their

smartphone were selected.

4.2 Reaction time (RT) tasks

During each drive in the simulator, participants were asked to respond to three auditory

tones and a red bar visual stimulus by pressing the clutch pedal as quickly as possible.

In the smartphone drive these stimuli coincided with social networking tasks:

Auditory reaction time task 1 coincided with Read message 1 in section 1

Auditory reaction time task 2 coincided with Write message 2 in section 2

Auditory reaction time task 3 coincided with Update status in section 3

Visual reaction time task coincided with Write message 4 in section 4

In the control drive, participants were given no social networking tasks to coincide with

the reaction time tasks. Thus, a comparison between the two drives was possible.

4.2.1 Response rate

Data for 220 reaction time tests were collected; 112 from participants’ control drives and

108 from their smartphone drives. Participants failed to respond to three of these tests

during the control drive, and 10 of the tests during the smartphone drive. These

differences are statistically significant (Fisher’s exact; p=.047) suggesting that

participants were more likely to fail to respond to reaction time stimuli while using their

smartphone. In real driving scenarios this has implications for drivers’ responses to

hazardous situations, and suggests that drivers may miss warnings or hazards.

4.2.2 Reaction times

On occasions where participants did respond to the auditory or visual stimuli, their

reaction times tended to be slower during the smartphone drives. Auditory 1 was

triggered during a read message task, Auditory 2 during a write message task, Auditory

3 during a status update task and the Visual stimulus during a write message task.



Figure 6: Mean reaction times

Paired samples t-test comparisons show that differences were statistically significant for

two pairs of the reaction time tests: Auditory 1 (t(24) = -2.242, p=.035) and Visual

(t(22) = -3.478, p-.002). Figure 6 illustrates these differences. These results suggest

that using a smartphone for social networking while driving can slow drivers’ responses

to events taking place on the road. The differences in reaction times between the two

drives were not statistically significant for Auditory 2 or 3.

4.3 Analyses of driving performance while using a smartphone

Participants were asked to interact with their phone on seven separate occasions during

their social networking drive. On four occasions they were asked to write a pre-defined

message, they were instructed to read messages on two occasions and they were also

asked to update their Facebook status.

As participants drove the same route in their control drives, it was possible to compare

driving performance in the sections where participants were interacting with their

smartphone, with driving performance at the exact same locations in the control drive.

Four key measures of driving performance were taken:

Mean speed

Standard deviation of speed (an indication of how variable speed was)

Standard deviation of lane position (an indication of variability of lateral position)

Maximum speed

For one section of the route, in which participants wrote their third message while

following a lead vehicle, the time headway between the driven vehicle and the lead

vehicle was also calculated.

The instructions to interact with their smartphone were pre-recorded and played at

exactly the same point along the route for each participant. As it was difficult to

ascertain the precise point at which participants started and finished using their phone,

the following assumptions were made to define the sections for analysis:

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Auditory 1 Visual

Reacti

on

tim

e (

sec)

Control

Smartphone



Smartphone interaction was assumed to start at the moment the pre-recorded

instruction ended

Smartphone interaction was assumed to end if participants looked up at the road

for an uninterrupted duration of at least 5 seconds

Statistically significant differences in driving performance are described below.

4.3.1 Mean speeds

Participants were instructed to write their first and fourth messages while driving in light

traffic along a motorway, their second message while following a series of curves at

40mph and their third message while following a lead vehicle at a constant distance.

Figure 7 shows participants’ mean speeds during these smartphone episodes.

Figure 7: Mean speeds during smartphone episodes

On average participants drove more slowly when writing messages on their smartphone

while driving (Write 1: t(23)=2.238, p=.035; Write 2: t(22)=2.626, p=.015; Write 3:

t(26)=2.134, p=.042; Write 4: t(25)=2.057, p=.05). This is consistent with previous

research which suggests that participants slow down in order to compensate for the

perceived impairment of using a phone while driving (see Chapter 2).

The difference in mean speeds for the two drives were not statistically significant for the

message reading or status update tasks.

4.3.2 Standard deviation of speed

Participants’ speed varied more in two sections of the smartphone drive when compared

with the control drive. These were while writing their fourth message (on a motorway in

light traffic) and updating their Facebook status (while following a lead vehicle whose

speed varied). Figure 8 shows these differences.

10

20

30

40

50

60

70

80

90

1st written 2nd written 3rd written 4th written

Mean

sp

eed

(m

ph

)

Control

Smartphone



Figure 8: Standard deviation of speed during smartphone episodes

Paired samples t-tests confirmed that these results were statistically significant (Write 4:

t(25)=-2.305, p=.03; Update status: t(26)=-2.736, p=.011), suggesting that

participants were slowing down and speeding up more while using a smartphone.

4.3.3 Standard deviation of lane position

Participants were asked to write their second message and read the second message

sent to them while following a curved section of road. They were asked to drive at

40mph and in the centre of their lane. While carrying out these smartphone tasks their

lane position varied more than in the same section of the control drive. The same

happened when they were writing their third message while following a lead vehicle on a

motorway. These differences are shown in Figure 9.

Figure 9: Standard deviation of lane position during smartphone episodes

Paired samples t-tests were conducted and the results showed that these differences

were statistically significant (Write 2: t(22)=-3.598, p=.002; Write 3: t(26)=-4.539,

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

4th written Status update

Control

Smartphone

.00

.10

.20

.30

.40

.50

.60

.70

.80

.90

2nd written 3rd written 2nd read

Sta

nd

ard

devia

tion

of

lan

e

po

sit

ion

Control

Smartphone



p=.000; and read 2: t(26)=-5.114, p=.000). No significant differences were found for

other smartphone tasks.

Further calculations were carried out to investigate the consequences of participants’

poor lane-keeping. It was found that participants crossed over the lane markings 26

times while using their smartphone to write the second message, but kept within their

lane at all times during their control drive. This is shown in Figure 10.

Figure 10: Number of lane excursions during 2nd written message

While writing their third message, participants crossed the lane markings four times, but

did not cross the lane markings in the same section of the road during their control

drive. They did not cross the lane markings at all while reading a message sent to them.

The deterioration in lateral control is consistent with results from other studies (see

Chapter 2) which have looked at the effects of distracted driving. This suggests that

driving while using a smartphone to write messages could pose a significant threat to the

safety of vehicles in adjacent lanes.

4.3.4 Maximum speed

The maximum speed that participants reached during each smartphone episode was

calculated but no significant differences emerged between these speeds and the highest

speeds reached in the same sections of the control drive.

4.3.5 Time headway

Calculations were also made to understand how well participants were able to follow the

lead vehicle while writing their third message. The results showed no difference in mean

time headway or the shortest time headway observed, but did show a difference in how

variable participants’ time headway was (t(26)=-3.291, p=.003).

0

26 excursions,

5 participants

0

5

10

15

20

25

30

Control Smartphone

Nu

mb

er o

f la

ne e

xcu

rsio

ns



Figure 11: Standard deviation of time headway

Figure 11 shows that time headway varied significantly more during the smartphone

drive, suggesting that participants were less able to respond to its changing speed. This

finding is consistent with the reaction time data, which also suggests poorer responses to

stimuli in the environment.

4.3.6 Gender differences

The sample of drivers tested contained an approximately equal number of males and

females. Thus, it was possible to investigate the relative effects of the smartphone tasks

on the driving performance of male and female participants. Repeated measures ANOVA

tests were carried out, with gender as a between-subjects factor.

In general, the data showed that there was a statistically significant difference between

males and females in the following measurements:

Standard deviation of time headway during the 3rd written message

(F(1,25)=4.909, p=.003)

Mean speed for write 4 only (F(1,19)=4.762, p=.042)

Standard deviation of lane position during write 2 (F(1,21)=4.372, p=.049), write

3 (F(1,21)=4.520, p=.046) and read 2 (F(1,25)=11.876, p=.002)

Standard deviation of speed during update message (F(1,25)=10.357, p=.004)

Key statistics in relation to these measures are presented in Table 10.

.00

.50

1.00

1.50

2.00

2.50

3.00

Control Smartphone

Sta

nd

ard

devia

tion

of

head

way



Table 10: Performance of males and females on key measures of driving

performance in each drive

Females Males

Measure Drive Section N Mean SD N Mean SD

SD time

headway Smartphone Write message 3 12 .97 .56 16 .48 .27

SD time

headway Control Write message 3 11 1.92 1.86 16 1.14 .76

Mean speed Smartphone Write message 4 11 71.22 3.10 16 74.49 5.05

Mean speed Control Write message 4 11 65.75 8.22 16 73.03 6.18

SD Lane Pos Smartphone Write message 2 10 .29 .07 14 .25 .06

SD Lane Pos Control Write message 2 9 .63 .44 14 .40 .10

SD Lane Pos Smartphone Write message 3 12 .25 .08 16 .17 .04

SD Lane Pos Control Write message 3 11 .37 .17 16 .24 .07

SD Lane Pos Smartphone Read message 2 12 .33 .09 16 .26 .08

SD Lane Pos Control Read message 2 11 .47 .14 16 .30 .07

SD Speed Smartphone Update message 12 2.42 1.09 16 1.69 .93

SD Speed Control Update message 11 3.33 1.08 16 2.20 .88

The results indicate that for these sections males tended to reduce their speed less, not

vary their lateral position, distance from the lead vehicle or speed as much as females

did. Thus, on these measures of performance, females did not perform as well as males.

Differences between the driving performance of males and females were not statistically

significant for any of the other measurements taken.

An interaction effect of drive and gender was found for only one of these variables:

standard deviation of lane position during the second read message task

(F(1,25)=11.582, p=.002). This suggests that the smartphone task affected males

differently to females, with females’ performance deteriorating more than that of males.

4.4 Visual behaviour

A video recording of each participant was taken during the drive and this made it

possible to observe their visual behaviour. Of particular interest were the sections of the

smartphone drive in which participants were interacting with their phone, and the same

locations in the control drive. The video was coded to compute the following variables for

each smartphone episode:

Total time spent looking down (this does not distinguish between looking at the

phone or other parts of the in-vehicle environment)

Total time spent looking up (ie at the road, mirrors, etc)

Duration of interaction with phone (sum of the above)



On average, participants spent 28.36 seconds per smartphone episode looking down

when compared with an average 5.1 seconds looking down in the same sections of the

control drive. Table 11 shows how this breaks down across all episodes of smartphone

use and also gives the same information about the comparable sections of the control

drive.

Table 11: Amount of time (in seconds) spent looking down during the

messaging section of the smartphone drive and equivalent section of the

control drive (note: message completion times not equal)

Drive Smartphone

episode N Minimum Maximum Mean

Std.

Deviation

Sm

art

phone

Write 1 24 14.14 46.99 31.34 10.37

Read 1 26 2.42 40.81 16.25 10.08

Write 2 27 5.90 77.91 30.73 14.76

Read 2 25 4.60 36.32 12.55 7.68

Update 27 20.02 92.54 41.55 14.97

Write 3 27 20.64 66.33 34.47 11.52

Write 4 27 15.90 119.52 30.40 20.28

Contr

ol

Write 1 20 .91 10.23 4.68 2.31

Read 1 19 .00 8.74 3.50 2.75

Write 2 25 .00 20.00 6.83 4.45

Read 2 27 .00 13.65 3.07 3.19

Update 27 .00 27.11 6.53 5.62

Write 3 27 .00 14.54 4.59 3.17

Write 4 27 .00 15.13 4.51 3.58

It can be seen that on average, participants spent longer looking down during sections of

the smartphone drive. Figure 12 displays the time participants spent looking down as a

percentage of the time they were interacting with the phone during that episode of

phone use. This accounts for the fact that each smartphone episode lasted a different

length of time.



Figure 12: Percentage of time spent looking down during the messaging section

of the smartphone drive and equivalent section of the control drive

It is clear that on average, participants spent between 40% and 65% of their time

looking down during smartphone episodes, when compared with under 15% of time

when not using a smartphone. Paired samples t-tests were used to investigate whether

these differences in visual behaviour between the smartphone and control drives were

statistically significant. Table 12 shows that for all smartphone episodes, the differences

were highly statistically significant. Participants spent much longer looking down when

using a smartphone than when not using a smartphone.

Table 12: Results of statistical test comparing the percentage of time spent

looking down

Smartphone

Mean (SD)

Control

Mean (SD) df t p

Write 1 55.3% (9.0%) 9.0% (4.3%) 19 21.275 .000

Read 1 48.5% (11.4%) 7.9% (6.7%) 21 15.483 .000

Write 2 46.6% (12.9%) 10.6% (6.4%) 24 13.300 .000

Read 2 42.5% (10.2%) 12.0% (9.5%) 23 11.074 .000

Update 62.2% (7.87%) 9.9% (7.5%) 25 24.599 .000

Write 3 60.6% (8.2%) 8.6% (5.4%) 25 26.874 .000

Write 4 58.9% (7.2%) 10.3% (6.7%) 24 29.428 .000

Although in the smartphone drives it is not possible to distinguish between time spent

looking at the phone and time spent looking at driving-related targets inside the vehicle

(such as the speedometer), it can be assumed that the control drive represents

participants’ normal visual behaviour. Thus, the difference between the two drives

represents the distraction from driving caused by use of the smartphone. This change in

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Write 1 Write 2 Write 3 Write 4 Update Read 1 Read 2

Percen

tag

e o

f ti

me s

pen

t

loo

kin

g d

ow

n

Control

Smartphone



visual behaviour fits well with the findings that measures of driving performance suffered

while participants were using a smartphone.

From some of the videos it was also possible to glean where participants were holding

their phone while using it. Some tended to place it against the top of the steering wheel

whereas others held it lower down or to one side. However, it was not possible to

pinpoint the location of the phone during all drives, so statistical analysis of the effects of

phone location was not conducted.

4.5 Effects of driving on smartphone use

Although the primary aim of this research is to investigate the effect of smartphone use

on the task of driving, carrying out two tasks at once can lead to reductions in

performance on both tasks. To investigate this, participants’ recall of the messages they

sent and the time it took them to compose messages was investigated.

4.5.1 Recall of received messages

During the trial participants were sent two messages and were prompted in the post-trial

questionnaire to recall a key fact from each message. All participants responded to the

question. Table 13 shows that only one participant (a different participant in each case)

was unable to recall the content of the message.

Table 13: Participants' recall of the messages sent to them

No. respondents No. Correct No. Incorrect

Message 1 28 27 1

Message 2 28 27 1

This demonstrates that, on the whole, participants did pay attention to the content of the

message.

4.5.2 Time taken to write messages

The second measure taken to assess performance on the task of writing messages was

the time it took to do so. Figure 13 shows that participants took on average just under

14 seconds to write the control messages, but when driving, it took them on average

56.6 seconds to write messages of a comparable length.



Figure 13: Average time taken to write messages while driving and control

messages while not driving

A paired samples t-test confirmed that these differences were statistically significant

(t(27)=-18.937, p=.000). Thus, it would seem that the task of driving also interfered

with use of the smartphone.

4.6 Subjective effects of smartphone use on driving performance

After each drive, participants were asked eight questions in which they had to rate

specific aspects of their driving performance. Table 14 shows the questions participants

were asked, their responses for each drive (mean and standard deviation) and results of

paired comparison t-tests.

.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Baseline Driving

Tim

e (

secs)



Table 14: Subjective ratings of performance during the two drives

Question Smartphone

Mean (SD)

Control

Mean (SD) t df p

Compared to how you normally

drive, how well do you think you

drove in the first motorway

section?

47.6 (21.1) 61.6 (20.5) -2.938 27 .007

How easy or difficult was it to drive

at 40mph and stay in the centre of

the lane during the curve following

task?

36.6 (16.9) 54.8 (21.1) -3.860 27 .001


drive on curved roads, how well do

you think you drove during the

curve following task?

29.2 (17.7) 46.8 (21.4) -3.607 27 .001


drive when following other

vehicles, how well do you think you

drove in the car following section?

45.3 (20.1) 55.4 (21.5) -2.234 27 .034

How easy or difficult was it to

maintain a constant distance

during the car following task?

34.8 (16.3) 42.4 (21.1) -1.791 27 .085


respond to any tones you might

have heard?

50.7 (20.6) 58.0 (21.3) -1.892 27 .069


respond to the red bar stimulus

which you might have observed?

41.6 (22.1) 56.0 (20.6) -2.878 27 .008


drive, how well do you think you

drove overall?

41.2 (19.4) 55.6 (16.5) -3.341 27 .002

The results show that participants tended to feel that their performance was worse

during the smartphone drive. All but two results are statistically significant. The

differences between their ratings for the two drives of their ability maintain a constant

distance during the car following task and the ease of responding to auditory tones failed

to reach statistical significance. These perceptions do not match the measures taken

from the simulator, which show significant delays in responding to the first auditory tone

during the smartphone drive. Thus, participants’ actual performance may be have

deteriorated even if they do not perceive this to be the case.



Aside from asking participants how they performed during each drive, the questionnaire

also asked how they felt social networking affected different aspects of their driving.

Table 15 presents participants’ views of the effect of social networking on their

concentration towards driving, its effect on their speed, headway, lane keeping, hazard

awareness and overall driving performance.

Table 15: Participants' perceptions of the effects of social networking on

driving

N Min Max Mean SD

Concentration

(high score means increased

concentration)

Updating status 28 1.1 13 4.35 2.71

Reading messages 28 0.5 9.8 4.83 2.49

Writing messages 28 0 9 2.78 1.99

Effect on speed

(high score means increased speed)

Updating status 27 0.2 73 6.74 13.54


Writing messages 28 0 8.6 3.74 2.53

Effect on headway

(high score means driving closer to car

in front)

Updating status 27 0 8.8 3.99 2.79

Reading messages 28 0 8.4 3.34 2.17

Writing messages 28 0 8 3.07 2.36

Effect on lane keeping

(high scores represent struggling to

maintain lane position)

Updating status 28 5.6 9.9 7.80 1.27


Writing messages 28 4.3 62 9.69 10.34

Effect on awareness of hazards

(high scores represent being less aware)

Updating status 28 0.9 9.5 7.45 1.77

Reading messages 27 1 9.6 6.34 2.02


Overall driving performance

(high scores represent worse driving

performance)

Updating status 28 2.8 10 7.79 1.54

Reading messages 28 4.8 10 7.19 1.51


The scores indicate that participants thought social networking negatively affected their

concentration, lane keeping, hazard awareness and overall driving performance. They

also reported that they left more distance between themselves and lead vehicles.

4.7 Patterns of mobile phone use

The post trial questionnaire enquired about participants’ patterns of mobile phone use, in

order to establish their level of familiarity with the device and the tasks they were asked

to perform during the trial.

4.7.1 Familiarity with the device

On average, participants reported that they had owned their phone for just over a year

and a half (Mean = 1.6, SD=1.3). Only one participant had owned their phone for one



month or less, suggesting that the vast majority of the sample was familiar with their

phone.

Participants were given four messages to write while they were not driving. On average

it took participants 13.9 (SD=4.93) seconds to write these messages. Figure 14 shows

the time taken for each of these four messages.

Figure 14: Mean and standard deviation of time taken to write baseline

messages

Figure 15 shows the distribution of participants’ mean baseline message writing times.

Figure 15: Boxplot of time taken (in seconds) to write messages when not

driving

0

5

10

15

20

25

Message 1 Message 2 Message 3 Message 4

Tim

e (

secs)



This shows that participants 16 and 22 took longer to write messages than the

remainder of the participants. However, the time it took them to write messages during

the drives was within two standard deviations of the sample mean. Thus, there is no

basis for concern that they were engaging in the secondary task of using their phone for

longer than the rest of the sample.

4.7.2 Familiarity with social networking and different phone functions

In order to ascertain whether participants were familiar with social networking sites, they

were asked how often per week they accessed social networks. All participants were

users of social networking sites and just under half accessed social networking sites over

thirty times per week (see Figure 16). This suggests that participants were familiar with

social networking sites.

Figure 16: The number of times per week participants access social networking

sites

It was also of interest to know how often they used their smartphone for basic mobile

phone functions as well as for social networking. Figure 17 shows the frequency with

which participants reported using their phone for spoken conversations, texting and

social networking.

0

2

4

6

8

10

12

0 1-5 6-10 11-20 21-30 31+

Nu

mb

er o

f p

arti

cip

an

ts

Number of times per week



Figure 17: The number of times per week participants access social networking

sites via their smartphone

More participants reported texting very frequently (31+times a week) than they did

using their phone for spoken conversations or social networking. Nevertheless, all

participants reported that they use their smartphone to access social networking sites at

least once per week. In fact, the results suggest that participants use their phone to

access social networking sites about as often as they do for spoken conversations.

Participants were asked to rate the ease of using their smartphone to access social

networking sites on a scale of 0 – 100 (0=very difficult, 100 = very easy). The average

score given by participants was 76.7 (SD=28.7). Nevertheless, there were four

participants who gave a rating of 20 or less.

4.7.3 Use of phone while driving

Participants were asked a series of questions about their use of mobile phones while

driving, including:

Do you take your smartphone with you when driving?

How often do you leave your smartphone switched on while driving?

If you leave your phone switched on while driving, how often do you leave it on

silent?

Do you have a cradle for your phone in your car? If so how often do you use it?

Do you use your phone hands free while driving

Do you access social networking sites while driving?

All participants reported that they take their smartphone with them when they are

driving. The overwhelming majority responded that they always leave their phone

switched on, while only two participants said that they ‘often’ leave it switched on. Only

nine of the 26 respondents to the question reported that they always or often keep their

phone on silent while they are driving. Leaving a mobile phone (and its ringer) on while

driving could present a temptation to use it.

0

2

4

6

8

10

12

14

16

18

0 1-5 6-10 11-20 21-30 31+

Nu

mb

er o

f p

arti

cip

an

ts

Number of times per week

Spoken conversations

Texting

Social networking



In the UK it is currently illegal to use a hand-held mobile phone while driving. Only six

out of 25 respondents to the question reported that they have a cradle in their car for

their mobile phone, and of these six, only two reported that they always use it. Thus, if

they do use their mobile phone while driving, the majority of participants in this study

would be at risk of non-compliance with the law.

Participants were asked whether they access social networking sites while they are

driving. Figure 18 shows that three of the 21 participants who responded to this question

said they do.

Figure 18: The number of participants who access social networking sites while

driving

While this is not a large proportion of drivers in this study, it does suggest that social

networking is an activity that some people engage in while driving. Thus, this activity

cannot be ruled out as a safety risk on the grounds that people don’t do it.

4.8 Perceptions of legality

In the post-trial questionnaire participants were asked whether they thought certain

activities are illegal, and whether they think these activities should be illegal. These

activities were:

Writing a message while the phone is in a cradle

Reading a message while the phone is in a cradle

Writing a message using the phone handheld

Reading a message while using the phone handheld

Writing a message using a text-to-speech function on the phone

Twenty-seven participants answered these questions. Figure 19 shows that a majority of

participants thought that it was illegal to read or write messages regardless of whether

the phone was in a cradle or used handheld. Perceptions were more mixed in relation to

use of the text-to-speech function, with more people being unsure or thinking it was a

legal activity than with the others.

0

2

4

6

8

10

12

14

16

18

20

No Yes

Nu

mb

er o

f p

arti

cip

an

ts

Whether participants access social networking

sites while driving



Figure 19: Perceptions of current legality of phone use while driving

In fact, current legislation does not specifically prohibit use of a phone to send and

receive text messages; the only requirement is that the phone is in a cradle. The

Highway Code does, however, advise that, “it is far safer not to use any telephone while

you are driving or riding – find a safe place to stop first or use the voicemail facility and

listen to messages later.” (DirectGov, 2011)

Figure 20 shows that participants’ perception of the current legality of these activities

was well-aligned with their opinions on whether the activities should or should not be

legal.

Figure 20: Perceptions of whether phone use while driving should be legal

Most participants thought that use of a phone to write or read messages should be

illegal, although more participants thought that writing messages using text-to-speech

functions should be legal than other activities (14 participants compared with 24-26

participants for the other activities).

0

5

10

15

20

25

30

write (in

cradle)

read (in

cradle)

write

(handheld)

read

(handheld)

write (text to

speech)

Not sure

Illegal

Legal

0

5

10

15

20

25

30

write (in

cradle)

read (in

cradle)

write

(handheld)

read

(handheld)

write (text to

speech)

Not sure

Illegal

Legal



4.9 Perceptions of relative risks of driving behaviours

Participants were asked to judge the difference that sixteen driving behaviours make to

a person’s safety while driving. The response scale was from 0% (less dangerous) to

100% (more dangerous). The results for this section of the questionnaire are presented

in Table 16.

Table 16: Participants’ judgements of the safety of different driving behaviours

Activity

Mean

percentage

risk

When a driver has been drinking alcohol (regardless of amount) 91.1%

When a driver is racing others 86.4%

When a driver is updating a social networking site whilst driving 86.1%

When a driver is tired 86.0%

When a driver is writing a text message 84.3%

When a driver is reading a text message 83.0%

When a driver is browsing a social networking site while driving 82.8%

When a driver is angry enough to have road rage 80.7%

When a driver is talking on their mobile phone (handheld) 78.9%

When other drivers on the road are acting unsafely 76.3%

When a driver is in a hurry 76.1%

When a driver is inexperienced 74.6%

When a driver is speeding 72.8%

When a driver is selecting music while driving 64.4%

When a driver is talking on their mobile phone (handsfree) 50.8%

When passengers are in the car 44.9%

Social networking activities ranked 3rd and 7th in the list, with updating a social

networking site being perceived as having a greater negative effect than browsing a

social networking site. All of the behaviours in this list, apart from those relating to social

networking, were included in the questionnaire administered during the study by Reed

and Robbins (2008). These results are broadly in line with their findings.



5 Discussion

This study set out to investigate whether there was an effect of social networking using a

smartphone on driving performance. Twenty-eight young male and female participants

took part in the study and drove a high fidelity driving simulator through the same test

scenario twice: once while using a smartphone to interact with a social networking site,

and once without this distraction. This experimental approach allowed potentially

hazardous road situations to be designed and experienced twice, in complete safety.

The results of the experiment clearly show that participants’ driving performance was

impaired by the concurrent smartphone task, and the smartphone task was also affected

by driving.

Participants were more likely to miss the reaction time stimuli while using their phone.

When they did respond, reaction times to visual and auditory stimuli were found to

increase from approximately 1.2 to 1.6 seconds when using a smartphone to send and

receive messages on a social networking site. This finding is consistent with other

studies that have looked at the distracting effects of spoken conversations and text

messaging using a mobile phone (Burns et al., 2002, Reed and Robbins, 2008). When

driving, failing to respond to a warning or hazard can lead to accidents. The effect of a

delayed response will depend significantly on the circumstances. At motorway speeds,

for example, a delayed response of 0.4 seconds could result in an increased stopping

distance of 12.5m. This could make the difference between a near miss and an accident,

or increase the severity of an accident.

During a section of the trial where drivers were following a series of long curves, control

of the vehicle suffered significantly when drivers were asked to send and receive

messages on a social networking site using their smartphone. They were unable to

maintain a central lane position and this resulted in lane departures. Over 47,000 road

traffic accidents in 2010 were single vehicle accidents in which the vehicle left the

carriageway (DfT, 2011). Of these, 734 resulted in at least one fatality. It is a concern

that as smartphones become more popular, distraction by reading and writing tasks

using these devices could lead to more accidents of this type. It was also interesting to

note that female drivers performed more poorly on this task. This is consistent with the

results of the Reed and Robbins (2008) study and may warrant further investigation.

Nevertheless, a performance impairment was found for both males and females,

suggesting that neither sex is immune to the distracting effects of using a smartphone

for reading and writing messages on driving.

Another key element of vehicle control in traffic is the time or distance to lead vehicles.

While using a smartphone to write a message, participants’ time headway varied

significantly more than during the control drive. In the simulated task the lead vehicle

was changing its speed, so this finding reinforces the data showing increased reaction

times while using a smartphone. Participants were unable to respond as quickly to the

speed changes as they were during the control drive. However, the lead vehicle varied

its speed fairly gradually, so the risk of a collision with the lead vehicle was very low in

the simulated scenario. The result suggests that in real world situations where a lead

vehicle may decelerate more quickly, there is the potential for accidents to occur due to

smartphone distraction.

During this study, participants tended to reduce their speed when using a smartphone to

read or write messages. This result is consistent with previous research (see Chapter 2)

and has been explained as an attempt to reduce risk due to a perceived increase in risk



resulting from engaging in a distracting activity. Fuller (2005) states that drivers adjust

their behaviour to keep the difficulty of the driving task within target boundaries. He

shows that drivers’ feelings of task difficulty predict their feelings of risk. The results of

this study seem to support this idea; when participants were given an additional task to

complete, they reduced their driving speed.

Even though the reduction in speed may be described as an attempt to compensate for

the effects of distracted driving, it is interesting that participants’ control of the vehicle

control was still worse in the smartphone drive. The reduction in speed was not enough

to compensate for the effects of smartphone use on their driving.

One of the reasons for the impairment in performance is clearly demonstrated by the

results of the analysis of visual behaviour. Drivers were found to be looking down

between 40% and 60% of the time while using a smartphone to write or read messages,

compared with about 10% of the time in the same sections of the control drive. Although

this study was unable to distinguish between glances to driving-related glance targets

(such as the vehicle instruments) and distractors, it can be assumed that the control

drive represents a normal amount of time spent looking at driving-related targets. Thus,

using a smartphone takes a significant proportion of drivers’ visual attention away from

the road, and this reduction in visual attention to the road environment is likely to be

one of the factors that contributes to poorer vehicle control and increased reaction times

to visual stimuli.

Most of the participants who took part in this study indicated that they very frequently

use their phone for text messaging. They reported that they engage in text messaging

more often than voice calls or social networking. Indeed they tended to use their phone

for social networking about as frequently as they did for voice calls. This shows that

whereas voice calls used to be the primary function of telephones, they are now just one

of a plethora of functions. Only a small number of participants from this study admitted

to accessing social networking sites while driving, but increases in the popularity of

online social networks could lead to a rise in the number of people engaging in this

distracting activity.

5.1 Comparison with previous studies

Previous studies of driver impairment conducted at TRL have used similar investigative

methods to those described here. Thus, it is possible to compare the relative impairment

of using a smartphone for social networking to the following:

Driving impairment while having a mobile phone conversation and impairment

from being at the legal limit for alcohol consumption (Burns et al., 2002)

Driving impairment from being under the influence of cannabis (Sexton et al.,

2000)

Driving impairment from sending and receiving text messages while driving (Reed

and Robbins, 2008)

The texting study and the current study are almost identical in methodology, allowing a

comparison across a broader range of measures.

Reaction times were assessed in all three previous studies. Although for the mobile

phone conversation and cannabis studies the reaction time tasks were slightly different,

they were still comparable. The same visual stimulus was used and was presented in the



same visual scene. When the reaction times under each condition were compared with

the baseline reaction times measured, alcohol gave a 12.5% increase in reaction times,

cannabis a 21% increase, a hands-free mobile phone conversation increased reaction

times by 26.5%, texting by 37.4%, using a smartphone for social networking by 37.6%

and using a mobile phone for a hand-held mobile phone conversation increased reaction

times by 45.9% compared to the baseline condition. Thus, using a smartphone for social

networking resulted in a greater impairment to reaction times than alcohol, cannabis,

hand held mobile phone conversations and texting, but less than a hand held mobile

phone conversation.

For measures of mean speed, standard deviation of speed and lane position, a direct

comparison with the earlier studies is difficult as the smartphone task only took place in

short bursts rather than over longer periods of driving. All studies reported a reduction

in mean speed and increase in standard deviation of lane position when compared with

the control condition.

A more detailed comparison can be made with the texting study as the experimental

scenario and messages composed on the phone were identical to those used in the

current study. Reed and Robbins (2008) reported a 5.7% reduction in mean speed

during the first message that participants wrote and 6.9% decrease during the fourth. In

the current study, a greater reduction in speed of 8.7% was observed when participants

were writing their first message, and a smaller reduction in speed (4.4%) when writing

their fourth message. Although none of the participants had to input usernames or

passwords to access their social networking accounts during the trial, it is possible that

searching for the message recipient in their contact list resulted in an additional task

load during their first message, and subsequent communication was therefore easier.

Reed and Robbins (2008) also commented on their participants’ lane position while

texting. Participants’ lane position varied 91.4% more when writing a message on a long

bend in the road, and 12.7% more when reading a message, when compared with the

control condition. In current study, writing the same message, at the same location in

the drive on a social networking site resulted in a 104% increase in the variability of lane

position, and reading the message at the same location resulted in a 37% increase in the

same variable.

All of the results taken together suggest that participants’ driving was impaired when

they were using a smartphone to send and receive messages on social networking site.

The results of this study indicate that this reduction in driving performance is likely to

have been a result of three different types of distraction: having to concentrate on the

smartphone task (cognitive distraction), holding the phone (manual distraction), and the

significant increase in time spent looking at the phone (visual distraction) in order to

interact with it. Although participants did reduce their speed, this was not enough to

compensate for the poorer driving performance; even though they were driving more

slowly, they were still unable to control the vehicle as well as they did when they were

not using their smartphone.

It is clear from the results of this study that certain tasks carried out using a smartphone

can significantly impair driving performance. In order to prevent drivers from becoming

distracted due to smartphone use, it may be possible to develop a smartphone

application which restricts access to some functions of the phone while driving. It may

also be beneficial to educate drivers about the dangers of distracted driving, and how

use of smartphones while driving can impair their performance.



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is driving with a mobile phone? Benchmarking the impairment to alcohol, TRL Report,

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Caird, J.K., Willness, C.R., Steel, P and Scialfa, C. (2008). A meta-analysis of the effects

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Chattington., M, Reed, N., Basacik., D. Flint., A. and Parkes, A. (2010). Investigating

driver distraction the effects of video and static advertising, PPR 409, Crowthorne: TRL

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Comscore (2011). GSMA Mobile Metrics Report Issued on UK Mobile Applications Usage.

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http://www.comscore.com/Press_Events/Press_Releases/2011/6/GSMA_Mobile_Media_

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Behaviour and Training. Paris, France: Cranfield University.

DirectGov (2011). The Highway Code. DirectGov [online], accessed 14th November 2011.

http://www.direct.gov.uk/en/TravelAndTransport/Highwaycode/index.htm

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(PA/3079/95) Crowthorne: TRL Limited. Presented at the Vision in Vehicles VI

Conference, 13-16 September 1995, University of Derby, UK

Fuller, R. (2005). Towards a general theory of driver behaviour, Accident Analysis and

Prevention, 37, 461-472.

Harbluk, J.L., Noy, Y.I. and Eizenman, M. (2002). The impact of cognitive distraction on

driver visual behaviour and vehicle control, TP No. 13889 E, Ottawa: Transport Canada.

Johnson, S.H. (undated). Effects of perceptual variables on the efficiency of human-

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http://www.csic.cornell.edu/201/touchscreen/

Klauer, S.G., Dingus, T.A., Neale, V.L., Sudweeks, J.D. and Ramsey, D.J. (2006) The

Impact of Driver Inattention on Near-crash/crash risk: An Analysis using the 100-Car

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Lesch, M.F. and Hancock, P.A. (2004). Driving performance during concurrent cell-phone

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http://www.comscore.com/Press_Events/Press_Releases/2011/6/GSMA_Mobile_Media_Metrics_Report_Issued_on_UK_Mobile_Applications_Usage

http://www.direct.gov.uk/en/TravelAndTransport/Highwaycode/index.htm

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Maples, W.C., De Rosier, W., Hoenes, R., Bendure, R and Moore, S. (2008). The effects

of cell phone use on peripheral vision, Optometry, 79, 36-42.

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market-reports/cmr11/?a=0

Owens, J.M., McLaughlin, S.B. and Sudweeks., J. (2011). Driver performance while text

messaging using handheld and in-vehicle systems, Accident Analysis and Prevention,

43(3), 939-947.

Parkes. A.M., Fairclough, S.H. and Ashby, M.C. (1993). Car phone use and motorway

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Taylor and Francis.

Parkes, A.M. and Hooijmeijer, V. (2000). The influence of the use of mobile phones on

driver situation awareness. National Highway Traffic Safety Administration (NHTSA).

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[online], accessed 10th August 2011 http://www-

nrd.nhtsa.dot.gov/departments/Human%20Factors/driver-

distraction/Topics023060002.htm

Parkes A.M., Luke T., Burns P.C. and Lansdown T. (2007). Conversations in cars: the

relative hazards of mobile phones, TRL Report 664, Crowthorne: TRL Limited.

Redelmeier, D.A and Tibshirani, R.J. (1997). Association between cellular telephone calls

and motor vehicle collisions. The New England Journal of Medicine, 336(7), 453-458.

Reed, N. and Robbins, R. (2008). The effect of text messaging on driver behaviour: a

simulator study, PPR 3667, Crowthorne: TRL Limited.

Sears. A. (1991). Improving touchscreen keyboards: design issues and comparison with

other devices, Interacting with Computers 3(3), 253-269.

Sears, A., Revis, D., Swatski, J., Crittenden, R and Schneiderman., B. (1993).

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Sexton, B.F. (1997) Validation trial for testing impairment of driving due to alcohol. TRL

Report 226, Crowthorne, TRL Limited.

Sexton, B.F., Tunbridge, R.J., Brook-Carter, N., Jackson, P.G., Wright, K., Stark, M.M.,

Englehart, K. (2000). The Influence of Cannabis on Driving. TRL Report 477,

Crowthorne: TRL Limited.

Strayer, D.L., Drews, F.A. & Crouch, D.J. (2006). A comparison of the cell phone driver

and the drunk driver. Human Factors, 48, 2, pp 381-391.

Tsimhoni, O., Smith., D and Green., P. (2002). Destination entry while driving: speech

recognition versus a touch screen keyboard, UMTRI-2001-24. Michigan: UMTRI.

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Appendix A Post-trial questionnaire



To be completed by TRL

Participant Number: ________________ Date of Trial: _____/_____/_________

Driving Simulator Study: SOCIAL NETWORKING WHILE

DRIVING

Note: All information on this form is confidential.

It will be stored securely at TRL.

No individuals will be identified.

SECTION A: BACKGROUND INFORMATION

A1. How old were you on your last birthday?

years old

A2. Are you:

Male Female

End of pre-drive section

Please wait for your trial supervisor



DRIVE 1

SECTION B: What do you remember about the text messages you

received?

You received two messages while driving; can you remember:

B1. What item of clothing did Edward forget for the wedding?

Hat Cufflinks Bowtie

B2. What medal did Fiona win in the 100m sprint?

Gold Silver Bronze

SECTION C: How you feel you performed during the drive in general

For each question, please mark the line in the place that you feel most closely reflects how you

feel about these behaviours. Please see below for an example.

Important: please try to describe how you felt you drove in general, not only at the times you

were using your phone.

EXAMPLE OF HOW TO COMPLETE SCALE

Please read the description of each end of the line and then mark a point which corresponds to

your answer. For example, if responsiveness and comfort were about equally important to you,

you might mark the scale below as follows:

Do you value comfort or responsiveness more when choosing a new car?

Responsivene

ss Comfort

C1. Compared to how you normally drive, how well do you think you drove in the first

motorway section?

Very poorly Very Well

C2. How easy or difficult was it to drive at 40mph and stay in the centre of the lane during

the curve following task?

Very difficult Very easy



C3. Compared to how you normally drive on curved roads, how well do you think you drove

during the curve following task?


C4. Compared to how you normally drive when following other vehicles, how well do you

think you drove in the car following section?


C5. How easy or difficult was it to maintain a constant distance during the car following

task?


C6. How easy or difficult was it to respond to any tones you might have heard?


C7. How easy or difficult was it to respond to the red bar stimulus which you might have

observed?


C8. Compared to how you normally drive, how well do you think you drove overall?


SECTION D: How you feel accessing social networking sites while

driving affected your performance during the trial


feel about these aspects of your drive.

D1. What proportion of your concentration were you directing to your smart

phone when updating your status?

Complete

concentration Virtually no

concentration


phone when reading private messages from Daniel?

Complete


concentration




phone when sending private messages to Daniel?

Complete


concentration

D4. Do you believe that updating your status affected your speed?

Drove slower Drove faster

D5. Do you believe that reading messages from Daniel affected your speed?


D6. Do you believe that sending messages to Daniel affected your speed?


D7. Did you keep the same distance to vehicles in front when updating your

status, or did it change?

More distance Less distance

D8. Did you keep the same distance to vehicles in front when reading

messages from Daniel, or did it change?


D9. Did you keep the same distance to vehicles in front when sending

messages to Daniel, or did it change?


D10. How did updating your status affect your ability to keep within your

lane?

Maintained

normal

positioning

Struggled to

maintain

normal

positioning

D11. How did reading private messages from Daniel affect your ability to

keep within your lane?

Maintained

normal

positioning

Struggled to

maintain

normal

positioning



D12. How did sending private messages to Daniel affect your ability to keep

within your lane?

Maintained

normal

positioning

Struggled to

maintain

normal

positioning

D13. When updating your status, did you feel there was a change in your

awareness of road hazards? (Remember to tick the centre of the line if

you feel there was no difference)

More aware Less aware

D14. When reading private messages from Daniel, did you feel there was a

change in your awareness of road hazards? (Remember to tick the

centre of the line if you feel there was no difference)


D15. When sending private messages to Daniel, did you feel there was a

change in your awareness of road hazards? (Remember to tick the

centre of the line if you feel there was no difference)


D16. How do you feel your driving performance changed when updating your

status?

Improved Worsened

D17. How do you feel your driving performance changed when reading

private messages from Daniel?

Improved Worsened

D18. How do you feel your driving performance changed when sending

private messages to Daniel?

Improved Worsened

Please stop here



DRIVE 2

SECTION E: How you feel you performed during the drive


feel about these behaviours. Please see below for an example.

EXAMPLE. Do you value comfort or responsiveness more when choosing a new car?

Responsivene

ss Comfort

E1. Compared to how you normally drive, how well do you think you drove in the first

motorway section?


E2. How easy or difficult was it to drive at 40mph and stay in the centre of the lane during

the curve following task?


E3. Compared to how you normally drive on curved roads, how well do you think you drove

during the curve following task?


E4. Compared to how you normally drive when following other vehicles, how well do you

think you drove in the car following section?


E5. How easy or difficult was it to maintain a constant distance during the car following?


E6. How easy or difficult was it to respond to any tones you might have heard?


E7. How easy or difficult was it to respond to any changes in your red bar stimulus which

you might have observed?




E8. Compared to how you normally drive, how well do you think you drove overall?


Any other comments?

SECTION F: How you feel about different driving behaviours

For each question, please mark the line in the place that you feel most closely reflects how you feel about

these behaviours.

What difference do you feel the following behaviours make to a person’s safety when

driving?

F1. When a driver is tired

Less dangerous More

dangerous

F2. When a driver is speeding

Less dangerous More

dangerous

F3. When a driver has been drinking alcohol (regardless of amount)

Less dangerous More

dangerous

F4. When a driver is talking on their mobile phone (handheld)

Less dangerous More

dangerous



F5. When a driver is reading a text message

Less dangerous More

dangerous

F6. Other drivers on the road are acting unsafely

Less dangerous More

dangerous

F7. When a driver is in a hurry

Less dangerous More

dangerous

F8. When a driver is inexperienced

Less dangerous More

dangerous

F9. When a driver is angry enough to have road rage

Less dangerous More

dangerous

F10. When passengers are in the car

Less dangerous More

dangerous

F11. When a driver is browsing a social networking application while driving

Less dangerous More

dangerous

F12. When a driver is writing a text messaging

Less dangerous More

dangerous

F13. When a driver is talking on their mobile phone (hands free)

Less dangerous More

dangerous

F14. When a driver is racing others

Less dangerous More

dangerous

F15. When a driver is selecting music while driving

Less dangerous More

dangerous



F16. When a driver is updating a social networking site whilst driving

Less dangerous More

dangerous



SECTION G: Your driving behaviour

Please think about your driving over the past 12

months. For each of the statements please tick the

most appropriate box in each row. Remember, we

do not expect precise answers, merely your best

guesses; so please do not linger too long over any

one item.

Never

Hard

ly e

ver

Occasio

nally

Quite o

ften

Fre

quently

Alm

ost

alw

ays

G1. Attempt to overtake someone that you hadn’t noticed to

be signalling a right turn.

G2. Stay in a lane that you know will be closed ahead until the

last minutes before forcing your way into another lane.

G3. Miss “Stop” or “Give way” signs and narrowly avoid

colliding with traffic having right of way.

G4. Pull out of a junction so far that the driver with right of

way has to stop and let you out.

G5. Fail to notice that pedestrians are crossing when turning

into a side street from a main road.

G6. Drive especially close to the car in front as a signal to its

driver to go faster or to get out of the way.

G7. Sound your horn to indicate your annoyance to another

driver.

G8. Queuing to turn left onto a main road, you pay such close

attention to the mainstream of traffic that you nearly hit the

car in front.

G9. Cross a junction knowing that the traffic lights have

already turned against you.

G10. On turning left nearly hit a cyclist who has come up your

inside.

G11. Disregard the speed limit on a motorway.



G12. Fail to check your rear-view mirror before pulling out,

changing lanes, etc.

G13. Become angered by a certain type of driver and indicate

your hostility by whatever means you can.

G14. Become impatient with a slow driver in an outer lane and

overtake on the inside.



Never

Hard

ly e

ver

Occasio

nall

y

Quite o

ften

Fre

quently

Alm

ost

alw

ays

G15. Underestimate the speed of an oncoming vehicle when

overtaking.

G16. Race away from the traffic lights with the intention of

beating the driver next to you.

G17. Brake too quickly on a slippery road, or steer the wrong

way in a skid.

G18. Drive even though you suspect you may be over the legal

blood-alcohol limit.

G19. Disregard the speed limit on a residential road.

G20. Become angered by another driver and give chase with

the intention of giving him/her a piece of your mind.



SECTION H: Your beliefs about accidents

Please indicate your agreement with the following

statements by ticking the most appropriate box in

each row.

Str

ongly

dis

agre

e

Dis

agre

e

Som

ew

hat

dis

agre

e

Som

ew

hat

agre

e

Agre

e

Str

ongly

agre

e

H1. Driving with no accidents is mainly a matter of luck.

H2. Accidents happen mainly because of different

unpredictable events.

H3. People who drive a lot with no accidents are merely lucky;

it is not because they are more careful.

H4. The careful driver can prevent any accident.

H5. When a driver is involved in an accident, it is because

they did not drive correctly.

H6. If you are going to be involved in an accident, it is going

to happen anyhow, no matter what you do.

H7. Drivers do not have enough control over what happens on

the road.

H8. Most accidents happen because of mechanical failures.

H9. It is always possible to predict what is going to happen on

the road and so it is possible to predict almost any

accident.

H10 Accidents happen because the driver does not make

enough effort to detect all sources of danger while

driving.



SECTION I: How you see your self, and how you believe others see

you

Please use the rating scale to the right to describe

how accurately each of the below statements

describe you.

Describe yourself as you generally are now, not as

you wish to be in the future. Describe yourself as

you honestly see yourself, in relation to other

people you know of the same sex as you are, and

roughly your same age.

Very

Inaccura

te

Modera

tely

Inaccura

te

Neither

Inaccura

te n

or

Accura

te

Modera

tely

Accura

te

Very

Accura

te

I1. Am sure of my ground.

I2. Easily resist temptations.

I3. Have little to contribute.

I4. Love to eat.

I5. Tend to vote for liberal political candidates.

I6. Like to stand during the national anthem.

I7. Am able to control my cravings.

I8. Do things I later regret.

I9 Believe laws should be strictly enforced.

I10. Know how to get things done.

I11. Never spend more than I can afford.

I12. Excel in what I do.

I13. Never splurge.

I14. Believe that we coddle criminals too much.

I15. Misjudge situations.



I16. Believe that there is no absolute right or wrong.

I17. Believe that too much tax money goes to support

artists.

I18 Don't see the consequences of things.

I19. Rarely overindulge.

I20. Believe that criminals should receive help rather than

punishment.

I21. Often eat too much.

I22. Go on binges.

I23. Don't understand things.

I24. Don't know why I do some of the things I do.

I25. Believe in one true religion.

I26. Complete tasks successfully.

I27. Handle tasks smoothly.

I28. Believe that we should be tough on crime.

I29 Come up with good solutions.

I30 Tend to vote for conservative political candidates.



SECTION J: MOBILE PHONE USAGE

For the following questions, please tick the box which you feel is most appropriate.

Try not to think about any question for too long, your first instinct or which ever

answer seems closest at first glance will be fine.

J1. How many months and/or years have you owned a smart phone for?

months years

J2.

How many times each week do you use your smart phone for spoken

conversations? This includes times when you are driving (hands free

or handheld) as well as all the times you are outside of your car.

0 1 – 5 6 – 10 11 – 20 21 – 30 31+

J3.

How many text messages do you typically send or receive in one

week? This includes times when you are driving as well as all the

times you are outside of your car.

0 1 – 5 6 – 10 11 – 20 21 – 30 31+

J3.

How many times do you access social networking sites in a typical

week, using any computer or device? This includes times when you

are driving as well as all the times you are outside of your car.

0 1 – 5 6 – 10 11 – 20 21 – 30 31+

J4. How many times do you access social networking sites in a typical week,

using your smartphone? This includes times when you are driving as well as

all the times you are outside of your car.

0 1 – 5 6 – 10 11 – 20 21 – 30 31+

J5. How easy do you find it to use your smart phone for accessing social

networking sites in general?

Very

difficult Very easy

J6. Do you take your smart phone with you when driving?

Yes No



J7. How often do you leave your smart phone switched on when you are

driving?

Always Often Sometimes Occasionally Never go to J13

J8. If you do leave your mobile phone switched on how often do you

leave it on silent?

Always Often Sometimes Occasionally Never

J9. Do you have a cradle for your phone in your car? If so how often do

you use it when driving?

No go to J11 Yes Always Sometimes Never

J10. Do you use your phone “hands-free” when driving?


J11. Do you access social networking sites on your smartphone while driving?


J12.

Does your phone have a “speech-to-text” function (you speak a

message and your phone transcribes it for you), if so how often do

you use it when driving?


J13. Are there any features of your mobile phone which you feel make accessing

social networking sites difficult, or that you dislike? How would you like it

to be improved?



SECTION K: LEGALITY OF PHONE USAGE WHILE DRIVING

These questions are designed to ask you what you understand about the legality of

using your phone social networking sites whilst driving, and what you feel the law

should be.

Is it currently legal to use your phone whilst driving to…

Legal Illegal Not

sure

K1. …write a status update or other message if

it is in a cradle?

K2. …read a status update or other message if

it is in a cradle?

K3. … write a status update or other message if

you are using it handheld?




you are using a text-to-speech function?

Should it be legal to use your phone whilst driving to…

Legal Illegal Not

sure

K6. …write a status update or other message if

it is in a cradle?


it is in a cradle?





K10

.

… write a status update or other message if

you are using a text-to-speech function?



End of questionnaires

transport research laboratory - iam roadsmart · 3.7 smartphone task 10 3.8 overall design 14 3.9...

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