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Prolonging the Safe Driving of Older Peoplethrough Technology

Final Report

Written by

Charles Musselwhite and Hebba Haddad

The Centre for Transport & SocietyUniversity of the West of England, Bristol

October 2007


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Prolonging the Safe Driving of Older People through Technology: Final Report 2

Acknowledgements

Our biggest thanks goes to our all our participants for so much of their valuable time

and the interesting discussions.

Thanks to our recruitment team headed-up by Claire Musselwhite and also thanks for

those who helped organise and recruit our participants:

Age Concern Poole, in particular Thelma Green.

Age Concern Dorchester, in particular Wendy Hilton and Irene Moss.

Alison Pearman at Poole Borough Council for putting us in touch with Thelma

and Age Concern Poole.

McCarthy and Stone and in particular Mark Sebbage Manager, St Aldheims

Court, Swanage for his help in recruiting and setting-up the focus groups.

Thanks to everyone at SPARC, especially Professor Peter Lansley, Verity Smith, Dr

Richard Faragher and Dr Nicky Hewson, for their support during the project.

Thanks to Mike Bradley, Suzette Keith, Catherine Wicks, Reg Goodwin and Judy Wilson

for their support and the interesting discussion on our research journey.

Thanks to Chloe Hyde for help in providing the materials, especially for the board

game.


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4.2 Giving-up driving and travel needs - - - - 51

5. FINDINGS AND DISCUSSION: DRIVER AND DRIVING NEEDS OF

OLDER PEOPLE - - - - - - - - 58

5.1 Self-description of driving behaviour - - - - 58

5.2 Perception of others driving behaviour - - - 60

5.3 Issues and problems with driving - - - - 63

5.4 Giving-up driving - - - - - - - 69

6.FINDINGS AND DISCUSSION: ATTITUDES TOWARDS ADVANCED

VEHICLE DRIVER ASSISTANCE AND INFORMATION SYSTEM - 73

6.1 Perception of advanced driver assistance and

information systems - 73

6.2 Matching advanced driver assistance and information

systems to driver needs - 79

6.3 Expert opinion and attitudes towards advanced driver

assistance and information systems - 81

7. CONCLUSION - - - - - - - - 85

7.1 Mobility and travel needs of older people - - - 85

7.2 Driving needs of older people - - - - - 85

7.3 Advanced driver assistance and information systems - - 86

7.4 Concluding remarks - - - - - - 86


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8. THE ROAD FORWARDS - - - - - - - 88

8.1 Expanding research topics - - - - - 88

8.2 Expanding the research to include more people - - 90

8.3 Expanding reality - - - - - - - 91

REFERENCES - - - - - - - - - 92

APPENDICES - - - - - - - - - 106

Appendix A Participant Information Sheet - - - 106

Appendix B Background Details Questionnaire - - 110

Appendix C Phase 1 Wave 1 Focus Group Topic Guide - 114

Appendix D Driver Diary Example - - - - 120

Appendix E Telephone Interview Schedule - - - 122

Appendix F Phase 1 Wave 2 Focus Group Topic Guide - 126

Appendix G Phase 2 Interview schedule - - - 136

Appendix H Phase 3 questions - - - - 141


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Executive Summary

Introduction

The population of older people in the UK is growing in number and in

percentage of overall population and is expected to continue to grow well into

the future.

Older people are more mobile than ever before. As a result there is an increase

in both the number of older people driving and the percentage of older people

on the road.

However, older people are the most likely group to suffer mobility deprivation

and report most difficulties in accessing local amenities such as shops, banks and

hospitals. In addition, reduced mobility and independence has been shown to be

strongly correlated with symptoms of depression.

Contrary to popular belief older drivers do not present an excessive risk to

other road users. Older drivers engage in less risk-taking driving behaviours than

their younger counterparts. However, older people are more likely to be killed

or seriously injured in accidents, largely because of their greater physical frailty

(DfT, 2001).

There is a slight increase in the average number of accidents for over 60s which

increases the older the individual gets. Therefore, when mileage is taken into

account they are slightly more likely to be involved in accidents than those of

middle-age (DfT, 2001).

The increase in accidents can largely be explained by changes in physiological,

cognitive and psychological processes that are related to the ageing process.

New in-vehicle technology, termed Advanced Driver Assistance Systems (ADAS)

or Advanced Vehicle Control and Safety Systems (AVCSS), can help reduce the

likelihood of accidents. Studies on older drivers and such technology are scarce

and show mixed results.

Methodological Framework

After the completion of a comprehensive literature review the following gaps

are found in previous research:

(i) A tendency to treat the driver community as one homogenous group.


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(ii) Research has previously been technologically led, in a top-down manner, and

thus has been technocratic rather than transcendent.

(iii) The tendency to ignore attitudes of drivers which are imperative to adherence

and acceptance of the technologies.

(iv) The tendency for researchers not to use more than one or two objective

measures of behaviour and ignore people focused research methods such as

interviews and questionnaires.

(v) The tendency for research to be non-participatory.

To overcome this, a modifiedgrounded theory approach was adopted where

participants become co-researchers and participate throughout the research

process. In addition, the research was needs-led and began with a

comprehensive assessment of older drivers travel and driving needs and

requirements, as well as their attitudes and acceptability of potential new in-

vehicle technologies.

Consequently the aim of the project was:

To critically examine whether new technological advances in Advanced

Control and Safety Systems have the capacity to aid driver safety and

prolong driving for older drivers in the UK

Accordingly, underpinning the aim in light of previous research, this project

had the following objectives:

To develop knowledge on older peoples travel needs.

To develop knowledge on older peoples driving needs (physiologicaland cognitive needs).

To address how older peoples driving needs might be met with new

technologies, such as Advanced Vehicle Control and Safety Systems.

To develop knowledge on factors affecting older drivers confidence(including psychological needs).

To study how new technologies might help increase the confidence ofolder drivers.

To propose technology that meets older individuals driving needsenhancing safety and confidence in the driving task.


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To examine the generalisability and feasibility of developing these newtechnologies

Methodology

The complete project consisted of 3 phases. The first phase consisted of three

focus groups with current car drivers. Participants in these three focus groups

have taken part in two waves of meetings, a short telephone interview and a

diary task. Phase 2 consisted of interviews with older ex-drivers who for one

reason or another have stopped driving. The objective of these interviews was

to examine why individuals had stopped driving and proposing new technologies

to assess how useful they could have been prolonging their driving. Phase 3

used the E-Delphi Technique to examine the generalisability and feasibility of

developing the new technologies which have been outlined in phases 1 and 2

amongst a group of experts.

26 participants aged over 65 years took part in phase 1 of the research. Three

groups of 7-12 participants formed the focus groups. All areas were in Dorset a

largely rural county in the South of England with a large proportion of older

people. People were chosen from urban, rural and semi-urban areas. The

sample total consisted of 18 males and 8 females. Ages ranged from 68 to 90

years old (mean = 75 years old, SD = 5.7). All of the participants have a

current driving licence and own, or have access to, a car and drove on average

109 miles per week.

31 participants aged over 65 years took part in phase 2 of the research, 18

males and 13 females, with ages ranging from 65 to 92 years old (mean = 76

years old, SD = 4.3). All had given-up driving between 6 and 18 months prior to

the research being carried out. Participants were recruited from urban, semi-

urban and rural areas of Dorset, Devon and Cornwall, three largely rural

counties with a high proportion of older people, found in the South of England.

On average, participants drove 91 miles per week prior to giving-up driving.

18 experts were identified and contacted to take part in electronic Delphi

discussion 4 people from the focus groups, 8 from industry (4 defined as car

designers, and 4 as specifically defined as technology manufacturers), 6

academics (people from disciplines such as ergonomics, human factors,

transport psychology, engineering and sociology).


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Findings and Discussion: Travel Needs of Older People

The findings from this study suggest that older people travel for a variety of

reasons that seem to inhabit three main categories:practical (primary) needs,

social (secondary) needs and aesthetic (tertiary) needs.

Primary needs are the need to get from A to B, to access services, shops and

the like, in safety, comfort and reliability.

Social needs are the need for fulfilment, independence, control and status that

travel and the travel mode can fulfil.

Tertiary travel need is the need for travelling for its own sake; to enjoy viewing

scenery on the travel and to enjoy the physical act of movement and travelling.

Participants were very aware or conscious of practical needs and less aware of

social needs and even less aware of aesthetic needs. The implication of this is

that interventions aimed at meeting travel needs often only concentrate on the

most articulated primary needs and despite anxiety over this level of need

being met when older people give-up driving, this largely is not the case. Older

people continued to be able to travel to go shopping and access services.

However, social and aesthetic needs tended to go unmet as driving were given-

up.

Findings and Discussion: Driver and Driving Needs of Older People

On the whole the older drivers stated they were better than the average driver

and also they felt they were better than when they were younger drivers. They

felt they had a better attitude, less time-pressure and better hazard

perception skills and ability to read the road ahead due to experience.

Major issues included problems with signage, maintaining a consistent speed,

tiredness and fatigue, longer reaction times, parking, reversing, dazzle and

glare from the sun and other drivers lights at night, junctions (especially

joining motorways) and overtaking. A range of physiological, cognitive and

psychological reasons for these were discussed.

For those that had given-up driving, participants had on average given-up

driving at 74 years old, with the youngest giving-up driving at 65 and the oldest

at 91 years of age.


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Analysis of the interviews with ex-drivers (n=31) suggested four main triggers

associated with giving-up driving. The most common trigger was a form of self-

diagnosis (15 participants 7 male, 8 female), followed by the influence of

friends and/or family pressure (6 male, 3 female), resulting from an specific

incident or event (2 male, 3 female) or being forced by a medical professional

(3 male, 0 females).

Female drivers were more likely to decide themselves it is time to give-up

driving through self-diagnosis or due to a specific incident. Male drivers were

more likely than female drivers to need to be told to give-up driving.

Findings and Discussion Advanced Driver Assistance and Information Systems

Three areas of advanced driver assistance and information systems were found

to be useful in meeting driver needs. Displaying road speed in the vehicle with

additional speed cue a system linked to satellite that then displays the speed

in the vehicle and alerts the driver when the speed is about to be reached, or

has been reached or is over by a certain amount. Displaying road signs in-

vehicle a system linked to satellite that displays some of the key signs on the

dashboard or again by head-up display. Night Vision something that enhances

vision of the road at night and how this might be re-displayed to the driver

could be investigated.

A discussion on each of these with experts highlighted that older people tended

to want technology that would enhance feedback, and professionals would

rather have technology that took over part of the driving task.

Overall, it was decided that technologies that should be investigated further

included a system of auditory feedback on the current vehicle speed,

intelligent speed adaptation and a system showing road signs (either on

dashboard and/or through head-up display). Night vision was felt to add to

distractions amongst older drivers.

The next stage of research should continue to involved older people but look to

develop, prototype and test auditory feedback on vehicle speed, intelligent

speed adaptation and in-vehicle road-sign display.

Concluding remarks


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The project has added depth of knowledge about older peoples travel needs,

driving needs and attitudes to advanced driving technologies.

This is a useful anchor to future studies that may develop and prototype such

technologies. It also serves as an important platform for future research

addressing similar social and attitudinal issues that may mediate or enhance

the effect of technology in overcoming barriers to a fulfilling life and meeting

the needs of this important and growing number of individuals.

Potential technological advances resulting from this project could enable older

people to continue driving for longer, whilst retaining confidence in their

ability, and ensure that they are safe drivers.

In addition, the methodology has provided an opportunity for older people to

get involved in research in a thoroughly participatory manner which has

ensured that they feel able to shape the research and maximise benefits of the

research outcomes for themselves and their age groups.


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RESEARCH OUTCOMES TO DATE

Peer Reviewed Publications:

Musselwhite, C B A and Haddad, H. (in preparation).An Explorative Study into the

Mobility Needs of Older Car Drivers

Musselwhite, C B A and Haddad, H. (in preparation).A Qualitative Study of the Driving

Needs of Older Car Drivers

Conferences:

Musselwhite, C. B. A. and Haddad, H. (2008). A Grounded Theory exploration into the

driving and travel needs of older people. Proc. 40th Universities Transport

Study Group Conference, University of Southampton, Portsmouth, January

2008.

Musselwhite, C. B. A. and Haddad, H. (2007). Putting your Foot Down. Invited

presentation for the Help the Aged/Research into Ageing Workshop, Older

People on the Move, University of Reading, 19th September.

Musselwhite, C. B. A. (2007). Travel Independence in Car Dependent Times.an

exploration into how technology might help older drivers meet their travel

and driving needs. Invited presentation for the Research for a Better Age

Workshop, Hotel Penzance, Penzance, 10th August

Musselwhite, C. B. A. and Haddad, H. (2006). Prolonging safer driving through

technology: user views. Invited presentation for the Transport for Older People

Workshop, Leeds University, 26th October

Musselwhite, C. B. A. (2006). Prolonging safe driving behaviour through technology:

attitudes of older drivers. Presented at 26th International Congress of Applied

Psychology, Athens, Greece. 16th - 21st July.


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Kenyon, S. L. and Musselwhite, C. B. A. (2006) Prolonging Safe Driving through

Technology. Poster presented at the Older People in Rural Areas (OPeRA)

Research Conference, Taunton, 4th July.

Additional Reports:

Musselwhite, C. B. A. and Haddad, H. (2007). Prolonging the Safe Driving of Older

People through Technology. Interim report. February 2007. Bristol: Centre for

Transport & Society, University of the West of England.

Media Events:

August 9th 2007 - The Cornishman - article written about the SPARC research

August 6th 2007 - Appearance on BBC Radio Cornwall discussing older drivers travel

and driving needs.

Networks:

July 2006 onwards Part of OPeRA (Older People in Rural Areas) Research Network

February 2006 onwards Associate Member of the Centre for Research on Ageing,

University of Southampton


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1. INTRODUCTION

1.1 BackgroundThe population of older people in the UK, as indeed it is across the western world, is

increasing in number, and is expected to do so for the foreseeable future (ONS, 2006;

Tomassini, 2004). Over the last century the population aged 65 years and over in the

UK has increased five fold from 1.8 million in 1901 to 9.5 million in 2001, with the

oldest age group (aged 85 years and over) which is eighteen times more numerous

than in 1901 (Tomassini, 2004). The percentage of older people as a proportion of the

total population is also increasing; in 1901 those aged over 65 years made up 4% of the

population and the equivalent age group made up 16% in 2001 (Tomassini, 2004).Predictions suggest that this growth in number and percentage will continue to 12.7

million people aged over 65 in 2021, and 15.27 million people aged over 65 in 2031,

representing 14.2% and 16.2% of the total population respectively (Tomassini, 2004). In

addition, the number of over 85 year olds will increase to 1.8 million in 2021 and 2.5

million in 2031, representing 2.8% and 3.8% of the total population respectively

(Tomassini, 2004). Long-term forecasts predict that on average one quarter of the

population of OECD member countries would be aged 65 or more by the year 2050

(OECD, 2001); a figure which is slightly higher for the UK (28%).

Changes in lifestyle as a result of increased longevity and better health and social care

mean that older people being mobile later on in their life than ever before (Tomassini,

2004). The importance of mobility has been highlighted for all segments of life and

society and has been linked to life satisfaction and quality of life (Schlag,

Schwenkhagen and Trankle, 1996). In addition, older people are driving later on in

life and more miles than ever before (Tomassini, 2004). In the UK, 70 % of adults (an

estimated 32.2 million people) currently hold full car driving licences (DfT, 2006a). Atotal of 47% of adults over the age of 70 hold a driving licence, which has increased

from 32% in 1989 (DfT, 2006a). In the last 30 years there has been a significant

increase in drivers who are 65 years and over and this increase is most markedly found

amongst female drivers a 200% increase in male drivers and a 600% increase in

female drivers over 65 years (DfT, 2001; Oxley, 1991). This rise is expected to

continue, and Noble (2000) predicts that 4.5 million people over the age of 70 will

have a driving licence by 2030. However, older people are the most likely group to


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suffer mobility deprivation (DfT, 2001) and report most difficulties in accessing local

amenities such as shops, banks and hospitals (ONS, 2004). Quite often this is because

they have given-up driving as they feel unable to cope with such a complex and

demanding task.

1.2. Travel Behaviour of Older People

Reduced mobility prevents older people from carrying out their social activities as well

as practical day-to-day needs. The ability to be mobile and travel serves functions

including entertainment (such as travelling for travelling sake and to get out of the

house), participation (in clubs and organisations), independence (in allowing older

people to remain as self-sufficient as possible, not relying upon others to access vital

services) and social interaction (allowing older people to socially interact with friends,

not only as a means to an end, but also whilst travelling) (DfT, 2001). In addition,

owning a car enables drivers to have control over their travel, giving them the

potential to travel when and where they want (Webster, Gow, Gilhooly, Hamilton,

ONeill and Edgerton, 2002; Metz, 2000).

Mobility is therefore important to older people both socially and practically. Further,

the need to be mobile also fills psychological requirements. For instance, reduced

mobility and independence has been shown to be strongly correlated with symptoms of

depression (Fonda, Wallace & Herzog, 2001). Ling and Mannion (1995) suggest that a

reduction in individual mobility leads to a decrease in morale and an increase in

depression and loneliness. Being mobile, especially through car use, can increase

feelings of self-confidence, mastery and self-esteem and feelings of autonomy,

protection and prestige (Ellaway, Macintryre, Hiscock and Kearns, 2003). Driving can

be linked to identity; Siren and Hakamies-Blomqvist (2005) suggest driving and owning

a car is associated with masculinity, youthfulness, status and power. For older people

driving can be seen as an example of staying young or warding off old age

(Esienhandler, 1990) and can be linked to showing personal and financial status,

especially amongst male drivers (Rothe, 1994).

1.3. Driver Behaviour of Older People

Contrary to popular belief older drivers do not present an excessive risk to other road

users (Maycock, 1997). Older drivers engage in less risk-taking driving behaviours than


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their younger counterparts (OECD, 2001). However, older people are more likely to be

killed or seriously injured in accidents, largely because of their greater physical frailty

(DfT, 2001; Hewson, 2006). In addition, the psychological impact of this is more

pronounced than a younger person in a similar incident, as older people worry about

their safety more. Older drivers drive less than younger groups and when taking into

account mile for mile, there is a slight increase in the average number of accidents for

over 60s which increases the older the individual gets (Hewson, 2006). Therefore,

when mileage is taken into account they are slightly more likely to be involved in

accidents than those of middle-age (DfT, 2001; Hewson, 2006).

Driving is a complex task which requires many interlinking cognitive, perceptual and

physiological processes (McKnight and Adams 1970). Changes in these processes that

are related to the ageing process can make the driving task more demanding

increasing the likelihood of involvement in a road traffic accident. Physical and

cognitive ailments are often experienced by older drivers which affect their ability and

frequency of driving (DfT, 2001). Reductions in these abilities is a natural part of the

aging process, and can affect safety of driving in different ways (DfT, 2001; Lee, Lee,

Cameron and Li-Tsang, 2003). Physiologically this includes deterioration of eye-sight

such as problems with distance vision, sensitivity to glare, binocular depth perception

and colour sensitivity. This can lead to unreliable visual information which can

increase the likelihood of misjudgements and errors whilst driving. Restricted physical

mobility such as Arthritis, stiffer muscles can make it difficult to operate the car

safely. Cognitive function deficits may occur later in life including an increase in

problems with attention, working memory and a decrease in information processing

capacity (DfT, 2001). This can lead to older drivers having difficulty in making critical

decisions under time pressure and dealing with immense traffic conditions. This

slowing down in cognitive functions may be amplified by conditions such as Parkinsons

disease (DfT, 2003) and dementia (Elliott and Grayson, 2001, 2002). Medication for

ailments (age-related and not) may again create problems for driving (DfT, 2001,

2003, 2006c)

Older people may engage themselves in compensatory behaviour to reduce the effect

of these deficits on driving behaviour. This usually starts with driving less due to

retirement as there is no need to commute and travel for work. Older people often


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avoid situations and places where they do not feel comfortable with driving, this

include driving at night (Charlton, 2002), wet roads, rush hours and unfamiliar roads

(Fildes, Lee, Kenny and Foddy, 1994). Older drivers also report avoiding driving on

routes with roundabouts and gyratory one-way systems (Simms, 1993). Older drivers

also reduce the amount of multitasking and reduce the speeds at which they drive

(DfT, 2001). The ultimate sacrifice though, for (older) drivers who feel they cannot

continue to safely drive, is to stop driving altogether. The age at which this happens

is subject to much variation, though the average for this has been reported as 72.1

years (Rabbit, Carmichael, Jones, and Holland, 1996). Although usually some

physiological and cognitive impairment led the individual to have to give-up driving,

older individuals are often over-anxious about the driving task and give up driving of

their own volition, sometimes when little or no physiological or cognitive impairment

is seen (Monterde I Bort, 2004).

Older people have particular difficulty with a variety of behaviours, such as navigating

an unfamiliar route or being distracted (either by the radio, passengers or something

on the roadside) (see DfT, 2001 for review). Older people have problems maintaining

speed, tracking, positioning and reversing (Brendemuhl, Schmidt and Schenk, 1988).

Older people are also reported to have problems with merging onto motorways,

varying pace on country roads and traffic lights and priorities in cities (Schlag, 1993).

Junctions are also problematic for older people, and they are more likely to have

accidents at junctions (Hakaimes-Blomqvist, 1988), this is particularly true for

junctions with no traffic control (Maycock, Lockwood and Lester, 1991).

1.4. New Technologies and Driving

In-vehicle technology, such as advanced driver assistance systems (ADAS) and in-

vehicle information systems (IVIS) is rapidly growing. Previously researchers and

engineers looked towards technology to reduce the impact of accidents, (such as

collision design), but new technologies can assist reduce the likelihoodof potential

accidents. Advanced Driver Assistance Systems (ADAS) are technologies such as lane

departure warning systems, Collision warning systems, Adaptive cruise control (ACC).

In-Vehicle Information Systems (IVIS) can be either nomadic (such as PDAs, mobile

phones) or built in to the vehicle (satellite navigation systems). Table 1.1 lists 18 in-

car technologies with a short definition of what they do.


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Table 1.1 Description of a selection of Advanced Driver Assistance and Information SystemsName DescriptionAdaptive Cruise Control ACC maintains a constant speed and a constant distance to the vehicle in

front, unless you cancel it by braking or switching off. You set theparameters by a switch on the indicator stalk. Mercedes-Benz was the firstto offer such a system, under the Distronic name, but similar adaptivesystems are now offered by other manufacturers.

Additional Speed Cue Visual, Auditory, Haptic

A system that would alert you to certain speeds that you set. So you couldset it to 20, 25, 30, 40 and 60 mph, when you reached the speed you wouldbe alerted by a light, buzzer or slight resistance on the accelerator. Couldincrease or vary feedback for different speeds.

Automatic Gears Clutchless gear change automatically done by vehicle engine based onengine revs.

Automated HighwaySystem

On entering an automated highway the vehicle is taken over by a computer.Cars drive along in platoons. To leave a platoon (at an exit, say) indication

gives driver back the control. Also known as hands off feet off driving!Child/Animal detection Thermal images are created by a computer. Those in the range of animal

temperatures are displayed on a computer or via a head-up display on thewindscreen, so drivers are alerted to an animal being in the area or to exactlocation of the animal.

Computer Route Planner Software on the computer which will provide optimal route (based onpreferences e.g. priority for time saving, fuel economy etc.) for a journey route provided in terms of a list of instructions or a map.

Cruise control Conventional Cruise Control driver sets a speed and the vehicle willmaintain that speed unless overridden by pressing the brake or accelerator.

Dashboard Sign Display Displays the signs from the road-side on the dashboard (or through head-updisplay)

Dashboard Sign Display

and Sign Prioritisation

Displays the signs from the road-side on the dashboard (or through head-up

display) and prioritises them based on user preferences (could eliminatehazard, directional or speed signs for example)

Display road speed insidevehicle

The current road speed is displayed in the vehicle (usually on thespeedometer but could be anywhere on the dashboard or through a head-updisplay)

Display road speed insidevehicle and additionalspeed cue

The current road speed is displayed in the vehicle (usually on thespeedometer but could be anywhere on the dashboard or through a head-updisplay) and the driver is alerted (by sound, visual or haptic feedback) thatshe/he has reached the speed limit (or is about to reach it).

Fatigue Detection System Monitors eye movements to detect signs of tiredness or fatigue and alertsthe driver.

Intelligent SpeedAdaptation

Limits the speed of the vehicle to the current road speed. The driver cannotexceed the speed limit.

Lane Detection System Alerts the driver (via sound, visual or haptic feedback) if she or he is gettingtoo close to the edge of the lane she or he is driving in.

Night Vision Enhancement Uses infrared technology to provide a better picture of the outside projectedonto the windscreen.

Real-Time TravelInformation

Up to date real time traveller information provided in the car via satellitenavigation systems, so can be both real-time (up to date) and based onwhere the vehicle is.

Satellite NavigationSystem (e.g. Sat Nav)

Provides directional information in-vehicle either a set of instructions(voiced or displayed) or via a digital map.

Vehicle Detection System Detects vehicles close to the left or right hand side of your vehicle andbehind your vehicle and provides feedback through sounds, vision or haptic.


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The new technologies listed in table 1.1 can be grouped under three broad headings:

1) Physical: These are technologies that assist (or force) the driver by taking over part

of the physical aspect of the driving task e.g. Automatic gears, ACC, Cruise Control,

Lane discipline, night vision, fatigue detection.

2) External Information: These use external information and re-present it to the driver

in order to aid safety through providing additional feedback e.g. Addition speed cue,

automatic Highway System, Animal detection, Head-up display, Road speed in-vehicle,

ISA, Vehicle Detection System

3)Journey Helpers: These provide extra information about the route to the driver

including route planners, Satellite Navigation systems, RTI system

Such modern technologies can have a wide range of advantages. For example, studies

of Intelligent Speed Adaptation, Adaptive Cruise Control and Automated Highway

Systems have shown the potential for reduction in emissions from vehicles (e.g.

Carsten and Tait, 2000; Liu, Tait and Boddy, 1999). On road studies have found that

various new technologies can create reductions in excess speed and less speed

variance (e.g. Almqvist and Nygard, 1997; Persson, Towliat, Almqvist, Risser and

Magdeburg, 1993; Varhelyi and Makinen, 2001; Walln Warner 2006). As a result of

improved driving it is estimated that there will be a reduction in accident injury of

between 10% and 40% depending upon the technology used (Cartsen and Tait, 2000).

However, not all studies have proved to be so positive. For example, studies have

shown that although devices that limit speed create slower speeds overall, people

adapted by not slowing at corners and intersections (Varhelyi and Makinen, 2001), not

slowing as much as normally in poor weather (Comte, 2000) and drive with less

headway (Comte, 2000). In addition, cruise control can increase speeds (Van Arem,

Hogema, Vanderschuren and Verheul, 1996, Hogema and Janssen, 1996, Sayer,

Fancher, Bareket and Johnson, 1995, Ward, Fairclough and Humphreys, 1995).

Although in-vehicle technologies can reduce stress (such as with ACC, Satellite

Navigation systems), drivers feel frustrated with systems that take over too much of

the driving task leading to drivers feeling they are losing too much control (Comte,

1996; Comte, Wardman and Whelan, 2000; Varhelyi and Makinen, 2001). Research


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seems to conclude that the main concern with most new technologies is the worry

about letting go of the control of the car and worry about the trust in automation

(Beikiaris, Petica and Brookhuis, 1997).

New technologies also give the opportunity for cognitive resources to be freed up (as

with ACC and ISA) and to allow more focus on the road conditions (see Hoedemeaker,

1999). This can save money and also be beneficial for the environment, with route

guidance technologies avoiding wasted driving. However, the technology itself could

become a distraction and actually add to cognitive workload. Such in-vehicle

technology should improve driving performance and safety but not at a cost to mental

workload and situational awareness. Further, they must be usable and affordable.

1.5 New Technologies and Older Drivers

In 2001, the OECD said that new technologies can make a significant contribution to

improving the safety of older drivers (OECD, 2001, p.11). One of their

recommendations states that particular attention needs to be given to evaluating

new technologies to ensure that older people can use it comfortably (OECD, 2001, p.

12). New technologies as an aid to driving have tended to be developed with the

driving population considered as a homogenous group and therefore ignored older

driver needs and attitudes (Musselwhite, 2004a; 2004 b; Rumar, 1986). Therefore it is

unclear whether the technology would be accepted and used and would have benefits

in reducing physiological barriers, cognitive error and mental workload amongst older

drivers. Van Wolfelaar, Brouwer and Rothengatter (1990) found new technologies that

provided more information to the driver hindered performance for older drivers. With

regard to tasks that reduce workload by taking over driving tasks, Musselwhite (2004a,

2004b) found that older drivers perceived an increase in stress and a decrease in

concentration if they were to use Intelligent Speed Adaptation (a technology that

limits the speed to the speed limit) and Adaptive Cruise Control (which limits the

speed and distance to the vehicle in front). Early research, such as EDDIT (1993) and

TELEAID (1995), has shown that in-car navigational systems has assisted older drivers

to drive further, and also has allowed them to drive with more confidence.

Oxley and Mitchell (1995) evaluated technologies being trialled by older drivers. They

found that overall reactions were good to the new technologies and that route finders,


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navigational aids, collision warning systems and night vision devices were all received

favourably by older drivers. That said it is important that the technology is user-

friendly. It may be that the difference between success and failure of technology is in

the specific ergonomic design, and ergonomic design needs to take into account older

drivers (Pauzie, 2003).

Pauzie (2003) explored the ergonomics in the context of cars, new technologies and

older drivers. She carried out in-car experiments with younger and older people and

assessed each groups receptiveness to varying degrees of legibility conditions. She

found that making on-board systems in bigger fonts and simplifying dialogue is

beneficial to both older and younger drivers. Training programmes that allow older

drivers get familiar with new technology is a further way to assist the uptake of

advanced vehicle control and safety systems (Simoes, 2003). Older drivers should be

encouraged to take part in the specific re-training programmes and they should be

widely available.

The problem with technological advances is that is may unintentionally exclude groups

who cannot afford, understand and use the technology (OECD, 2001). Older people, in

particular, may feel excluded. It is therefore important that the travel needs of this

age group is examined to make sure that this ever-growing part of society can move in

parallel and allow technology to enable them to sustain a high level of mobility. To

this end, research into new technologies should involve the end-user throughout the

design process to ensure maximum success of technology (Howarth, 1993). There is a

very clear need for such research addressing appropriate technologies to aid safe

driving amongst the older driver population. Engineers and designers are often

younger individuals with little knowledge of older driver needs. A dialogue between

the users and designers is paramount in ensuring new technologies are as beneficial as

they potentially can be to prolong safe driving amongst older people. Further still,

older people do not reject new technology in cars which provide them with

information and help if the interaction is easy to understand (Pauzie, 2003). The

OECD of 2001 advises that older drivers need to be included in trials of new

technologies in cars as they are an increasing proportion of the driving population.


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This multi-method study will involve older drivers as participants to develop an

understanding of older peoples transport needs, particularly in relation to driving,

and how these may be addressed by technology, the types of technology required by

older drivers, their attitudes towards these technologies and the feasibility of any

suggestions made. It is hoped that the study will form a basis for new technologies to

be developed and existing technologies to be altered to better suit older drivers, thus

enabling them to prolong safe driving behaviour.


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2. METHODOLOGICAL FRAMEWORK

This section discusses the framework and context for which the methodology was

adopted in light of gaps and issues with previous research in the field. Aims and

objectives are then addressed to meet these gaps and a philosophical stance is

adopted outlining the epistemological underpinnings for the research to be carried

out. Ethical considerations for the research are also considered.

2.1. Gaps in Previous Research

Building on work examining research into technology and driving behaviour the

following limitations of previous research are noted (see also Musselwhite, 2004a,

2004b):

(i) The tendency to treat the driver community as one homogenous group;

(ii) Research has been technologically led, in a top-down manner, and thus has been

technocratic rather than transcendent;

(iii) The tendency to ignore attitudes of drivers which are imperative to adherence and

acceptance of the technologies;

(iv) The tendency for researchers not to use more than one or two objective

measures of behaviour and ignore people focused research methods such as interviews

and questionnaires;

(v) The tendency for research to be non-participatory.

2.1.1 The tendency to treat the driver community as one homogenous group

Previous research has tended to group together all the driving population as if they are

one whole that can be generalised from. There are some examples of identifying

different groups of driver and concentrating on individual differences. For example,

gender differences have been studied (e.g. Dingus, McGhee, Monakkal, Jahns, Carney,

and Hankey, 1997; Dobson, Brown, Ball, McFadden and Walker, 1999; Forsyth, Dowing

and Wells, 1990; Parker, Reason, Manstead and Stradling, 1995; Quimby, Maycock,

Palmer and Buttress, 1999; Reason, Manstead, Stradling, Baxter and Campbell, 1990;

Rolls, Hall, Ingham and McDonald, 1991), marital status has been looked into (Rolls

and Ingham, 1992), different aspects of driver and accident history have been

analysed (Fildes, Rumbold and Leening, 1991; Mourant and Rockwell, 1978; Quimby,

Maycock, Palmer and Buttress, 1999; Rolls and Ingham, 1992), and psychological


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profiles have been used (e.g. Parker et al., 1995; Reason et al., 1990; Quimby,

Maycock, Palmer and Buttress, 1999). However, when age is addressed (e.g. Parker et

al., 1995; Reason et al., 1990; Quimby, Maycock, Palmer and Buttress, 1999; Rolls et

al., 1991) categories used to identify stratification by age is often in a strictly limited

capacity i.e. the older driver is categorised as everyone over the age of 60 or 65 for

example and does not take into account the marked physiological and psychological

differences found between people beyond this age group. The notion that all over 60s,

for example, accurately reflect all older drivers is a misnomer, either greater age

stratification is required (e.g. 55-65, 65-75, 75-85 and 85+) or indeed other factors are

needed to be taken into account alongside age (health, socio-economic status, access

to public transport etc)

Research into Advanced Vehicle Control and Safety Systems (AVCSS) has failed to place

drivers into different categories and where it has done so the numbers who appear in

each category are so small that no differences can be regarded as reflecting the

population as a whole. This is unusual since AVCSS tends to be technologically focused

and market driven and the advantage of market segmentation for companies

developing such technologies is important in success. Studies on Intelligent Speed

Adaptation (ISA) in particular have tended to group the driving population together as

a whole (Almqvist and Nygrad, 1997; Cartsen and Tait, 2000; Comte, 1996; Comte et

al., 2000; Persson et al., 1993; Varhelyi and Makinen, 2001; Walln Warner 2006).

2.1.2 Research has been technologically led, in a top-down manner, and thus has been

technocratic rather than transcendent

Despite rhetoric to the contrary, much research still begins with the technology rather

than a thorough understanding of individuals needs and requirements that the

technology could ultimately meet (see Baggio, 2001; Biding, 2001; Bishop, 2001;

Grant, 2001; Sahala, 2001; Smith, 2001 for examples). Thus, research tends to be

technologically driven, rather than needs-led and as such there is often a mismatch

between technology and need resulting in at best poor uptake of the technology and

at worst dangerous behavioural adaptation, where negative unintended consequences

are found. As such a transcendent approach is required where initial studies begin

with a comprehensive analysis of driver needs and requirements (Neumann, 1997).

Technology should then be developed to fit these needs and Human Factors


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considerations continually researched throughout the design process. This should

ensure that the technology fits peoples needs and requirements and that the

technology is useable and fulfils its purpose (Haworth, 1993).

2.1.3 The tendency to ignore attitudes of drivers which are imperative to adherence

and acceptance of the technologies

Previous research into the success of engineering and technological interventions on

the road suggests peoples subjective interpretation and impression of them, often

measured or studied through attitudes, is vitally important (e.g. Marell and Westin,

1999, Musselwhite 2004a, 2004b). Negative or inappropriate attitudes towards

interventions reduces their likelihood to be used, adhered to and ultimately to be

successful. As such it is important that attitudes towards technology are collected

alongside other behavioural measures of success.

2.1.4 The tendency for researchers not to use more than one or two objective

measures of behaviour and ignore people focused research methods such as interviews

and questionnaires

Research into the success of technological interventions has often relied on one or two

objective markers, such as reduction in speed or reduction in headway. To capture a

rounded picture of success subjective impressions and thoughts need to be captured to

move beyond a simple evaluation to a critical understanding of the technology at the

human-user interface (Musselwhite, 2004a, 2004b).

2.1.5 The tendency for research to be non-participatory

Previous research has tended to be done on subjects rather than adopting a more

collaborative approach with participants. Thus, the research tends to be done to

people rather than with people. As such vital nuances of behaviour can be missed in

the researcher-researched gap, particularly when studying habitual behaviour which is

difficult to self-report, as with car driving behaviour. Involvement of end-users as

participants can occur at different parts of the research process, where end-users

move from the tradition of not being involved in the research, to advising the research

team; sitting on steering group meetings; acting in the capacity as researcher; to a

situation where the majority of the research team is made up of end-users. Research

tends to benefit the more involved end-users are in the process. For example,


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relationships with participants are more informal and friendly creating a much more

open situation where more appropriate and less managed or staged data is

generated (Polowycz, Brutus, Orvietto, Vidal and Cipriana, 1993; Secker, Grove and

Seebohm, 2001). In addition, end-users often see technology from a different

perspective, a much more real and grounded perspective, than researchers (Rose,

2003) thus creating greater understanding of the social context of peoples needs,

issues and requirements (Forrest, Risk, Masters and Brown, 2000). There are benefits

for the participants when they have more control over the project. They have a sense

that research about them is being carried out with them rather than on them and they

feel a sense of control, especially if they can see their work influencing policy and

practice. A sense of control over potential decisions and guidance for themselves is

linked to greater mental and physical well-being (see Langer and Rodin, 1976)

2.2. Aims and Objectives of the Project

2.2.1 Aim

Taking into account the literature review and the weaknesses of the reviewed

research, the aim of the project is:

To critically examine whether new technological advances in Advanced Vehicle

Control and Safety Systems have the capacity to aid driver safety and prolong driving

for older drivers in the UK

The aim can be studied in its parts as:

(a) Technological Advances in Advanced Vehicle Control and Safety Systems

This study keeps a fairly open definition of the term Advanced Vehicle Control and

Safety System (AVCSS). Any technology that is seen to aid driving is included, with a

particular focus on technology based on electronic engineering. In the nature of the

project, the definition will stem very much from the participants themselves, but are

likely to include the following:

(i) Current In-vehicle and Infrastructure Based Technology. Recent advances in

Global Positioning Systems (GPS) have resulted in a large uptake of on-board

Satellite Navigation Systems. Attitudes and acceptability of such technology,

from basic (automated maps) to dynamic (with real time information), will be

studied.

(ii) Future In-vehicle and Infrastructure Based Technology. A total of 18

technologies (as outlined in Table 1.1) will be studied. These technologies are


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based on off the shelf technology developments but will be attuned and

developed in light of the individual participant needs, requirements and

attitudes. These 18 technologies are broken into 3 categories: physical,

external information and journey helpers (see section 1.4).

(b) Aid Driver Safety

The project will look at how such technologies might (or indeed might not) aid driver

safety. It is primarily through attitudes towards such technology in light of needs and

requirements of drivers that this will be addressed; for example how can such needs

and requirements that may hamper safety by met through new technology such as

AVCSS. Robertson (2000) and Robertson and Robertson (1999) highlight that there are

three levels of needs and requirements and these are found as conscious, unconscious

and undreamed. Conscious needs and requirements are known to all and can easily be

collected by a researcher. Unconscious needs and requirements are those that are

assumed or expected and must be dug-out or elicited by a researcher. Undreamed of

needs and requirements are those not known by anyone. This assumes that

requirements are not just out there waiting to be collected or elicited and these

needs and requirements can be generated between people. Traditional training needs

analysis often involves observation, survey work and is largely quantitative in nature.

As such they collect conscious needs and requirements; this study will go beyond this

to concentrate exclusively on qualitative research techniques with the aim of

addressing in-depth unconscious and undreamed of needs.

(c) Prolong Driving

The project will look at how such technologies might (or indeed might not) allow or

encourage drivers to continue driving later on in their life. Drivers tend to give up

driving for a variety of reasons that can be grouped into physiological, cognitive and

psychological. Identifying such physiological, cognitive and psychological needs and

issues will be carried out. Again, it is primarily through attitudes towards such

technology in light of needs and requirements of drivers that this will be addressed;

for example how can such needs and requirements that may mean people give up the

driving task by met through new technology such as AVCSS.


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(d) Older Drivers

The focus of this research will be on the older driver. As established earlier, the

population of older people in the UK is increasing in number, and is expected to

continue to do so for the foreseeable future (ONS, 2006).

2.2.2. Objectives

Accordingly, underpinning the aim in light of previous research, this project has the

following objectives:

To develop knowledge on older peoples travel needs.

To develop knowledge on older peoples driving needs (physiological

and cognitive needs).

To address how older peoples driving needs might be met with newtechnologies, such as Advanced Vehicle Control and Safety Systems.

To develop knowledge on factors affecting older drivers confidence(including psychological needs).

To study how new technologies might help increase the confidence ofolder drivers.

To propose technology that meets older individuals driving needs

enhancing safety and confidence in the driving task.

To examine the generalisability and feasibility of developing these newtechnologies.

2.3. Philosophical Stance

2.3.1 Driving as a social behaviour

The study adopts the stance that driving is a social behaviour. Driving is seen as a

reflection of relationships and interactions occurring between people. To answer the

aim of the project an idiographic approach is taken involving intensive studying of

small groups in great detail. This lends itself to a predominantly qualitative research

project. The emphasis is not on comparisons between people but on building intensive

structures within the participant to ascertain the origins. Despite the obvious lack of

statistical rigour the qualitative method, it is no less scientific or empirical and

indeed overcomes many major methodological horrors or crisis found when the

subject of the research is similar to the researcher (i.e. they are both human) possibly

producing a more scientific approach (Banister, Barman, Parker, Taylor and Tindall


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1994). This is a radical departure from most transport research which concentrates

using an extensive design with predominantly quantitative research methods and

statistical analysis. Banister et al. (1994) define qualitative research as,

an attempt to capture the sense that lies within, and that structures

what we say about what we do, an exploration, elaboration and

systemisation of the significance of an identified phenomena

the illuminative representation of the meaning of a delimited issue

or problem. (P. 3)

Thus, the qualitative paradigm lends itself perfectly to an in-depth study of peoples

needs and perceptions with regard to transportation issues and in particular

technological Advanced Control and Safety Systems.

2.3.2. Epistemological stance

Despite the important role that human behaviour occupies within traffic and transport

systems, most research on vehicle driving behaviour has tended to be based on a

traditional positivist framework. Indeed, epistemology (knowing what does or does not

constitute as warranted knowledge) is rarely, if ever, discussed. The resulting

epistemological lethargy affords a one-dimensional research framework in which many

important areas of research, particularly those addressing the effects of subjective

appraisal (such as attitudes and motivation) on behaviour, are not being addressed.

To overcome this, a post-structuralist approach is proposed using a modifiedgrounded

theory approach, where participants become co-researchers and participate

throughout the research process (Strauss and Corbin, 1998; Glaser, 2001). This

approach suits the nature of generating and developing knowledge and meaning from a

wide variety of opinions and attitudes, without doing an injustice to their diversity and

depth. Strauss and Corbin (1998) describe grounded theory as a theory derived from

the data, systematically gathered and analysed through the research process

method, data collection, analysis, and eventual theory stand in close relationship to

one another. (Pg. 12). Glaser (2001) describes grounded theory as, the generation of

emergent conceptualised integrated patterns, which are denoted by categories and

their properties (Pg. 9). Therefore, a researcher does not begin with a preconceived

theory in mind, rather crafting theory from the rich collection of knowledge. The aim


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of grounded theory is to explain the knowledge from whence it came (Glaser, 2001).

The theory does not pretend to describe the data accurately, but to explain the

knowledge conceptually and contextually. Therefore, grounded theory is not a

research method but a framework on which to use and interpret findings using

appropriate methodology. Knowledge can be generated from using a variety of

methods. Descriptions of grounded theory vary, but the following procedures are

identified as important to follow (Glaser, 2001; Strauss and Corbin 1998)

(1) Decide upon topic area. The topic area is held in very general and abstract

terms. For this research, the topic area has been identified through the

researchers interest in psychology and transport and critically analysing

previous literature and research in this area (see section 1). Aims and

objectives can be crafted at this stage, but it is unusual to have testable

hypotheses (see section 2.2)

(2) Adopt a methodology. The next stage is to adopt a methodology that will

generate knowledge in a very open and general way around the topic area or

main concerns with the topic area (see section 3).

(3) Analyse and conceptualise knowledge. This can be achieved through

constant comparative analysis of data collected in the adopted methodology.

Conceptual themes can then be reported from the data (see sections 4-7)

(4) Contextualise knowledge. The knowledge needs to then be conceptualised

against previous literature and is given a framework to highlight where the

knowledge resides in relation to the wider picture. A summary of the

contextualised knowledge is followed by a discussion (see sections 4-7).

(5) Developing hypotheses. Conceptualised and contextualised knowledge can

then be investigated on different audiences to address its validity amongst

differing groups of people with differing perspectives. This occurred through a

discussion group in the format of a Delphi technique (see section 7).

The methodology varies to traditional positivist science in that knowledge about the

topic transcends the research. The main issues of concern are generated from the

methodology as much as they are from previous literature. Hypotheses are generated

after knowledge gathering and analysis, not before data gathering and analysis. This

approach seems appropriate when addressing a project on attitudes and perceptions,


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since a positivist approach would focus on a small area of data, rather than creating a

large knowledge base, which is more appropriate for attitudinal research.

2.4. Ethical Approval

Ethical approval for the project was awarded by the internal ethical council at the

University of the West of England, Bristol.

2.5. Research Framework

The complete project consists of 3 phases. Figure 2.1 (below) shows the plan of the

three phases and how they sit amongst each other. The first phase consists of three

focus groups with current car drivers. Participants in these three focus groups have

taken part in two waves of meetings, a short telephone interview and a diary task.

Phase 2 consists of interviews with older ex-drivers who for one reason or another

have stopped driving. The objective of these interviews was to examine why

individuals have stopped driving and proposing new technologies to assess how useful

they could have been prolonging their need to give-up driving. Phase 3 used the E-

Delphi Technique to examine the generalisability and feasibility of developing the new

technologies which have been outlined in phases 1 and 2 amongst a group of experts.


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Figure 2.1 The interlinking phases of research

PHASE TWO -

31 ex-drivers

Interviews

Why people gave-up driving

and assessing the feasibility oftechnologies

PHASE THREE -

18 users/experts

E-Delphi Technique

To examine the generalisability

and feasibility of developing thenew technologies

PHASEONE

-

26driving(3groups)

Driver DiaryReflecting on driving needs in practice

Wave 2 focus groupUnderstanding how driving needs

might be met with modern technology

Telephone InterviewsRe-visiting driving needs and assessing

attitudes to technology

Wave 1 focus groupUnderstanding older peoples driving

needs


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3. METHODOLOGY

3.1 Phase One Methodology3.1.1 Participants

During phase one, this project worked closely with older individuals, as defined in line

with Office National Statistics and UK government policy as 65 years of age and over

(ONS, 2004, 2006). The sample consisted of 26 individuals (18 males and 8 females),

with ages ranging from 68 to 90 years old (mean = 75 years old, SD = 5.7). Recruitment

took place by approaching people in town centres in well-lit areas in the middle of the

day, by professional recruiters and through help of charities addressing older people

issues, including Age Concern. Potential participants were given information sheetsexplaining the project and how they can get involved. The process was inline with

ethical codes of conduct throughout. In this way the project addresses three main

areas: informed consent (a letter to all participants and was distributed at the

recruitment stage and re-emphasised at the start of each focus group and telephone

interview), protecting the participants (the right to withdraw themselves, any

information or answers given at any time is allowed and this included after the focus

groups) and anonymity and confidentiality (transcripts of the focus groups written by

the research team are anonymous). Given that a great deal of the participants timeand effort was required, participants were paid 30 for their involvement.

Participants were recruited from urban, semi-urban and rural areas in Dorset, a largely

rural county in the South of England with a large proportion of older people. Dorset

was chosen for ease of access to older people and as a known area with accessibility

difficulties for older people. All of the participants had a current driving licence and

own, or had access to, a car. Most (89%) of the participants own their home out right

with 12% saying they owned their house with the help of a mortgage. Most (69%) livedas a couple and 27% said they lived alone. 65% said their health was good, 15% said

their health was fair and 19% of participants said that their health was excellent.

Table 3.1 shows the average amount and type of driving reported by the participants.

On average, participants drove 109 miles per week, ranging from 20 to 400 miles. This

compares favourably to the national statistics on driving in the UK; older drivers (aged

65 and over) drive around 102 miles per week on average (DfT, 2006a). In this study


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participants completed 8.5 journeys by car, on average, per week. All participants

were asked to respond to how much in terms of a percentage they used their car for

certain purposes e.g. work, social, services, other. Most people in this sample used

their car for social purposes (the average response was 42%). The average percentage

given to services was 31%. The average for work purposes was 10%, for other

(responses included things such as sightseeing and pleasure) purposes the average

percent was 13%. This reiterates the notion that driving for older people is crucial for

social activities and amenities.

Table 3.1: Background statistics of the participants

Participant MeanAverageNumber of

..miles driven/week 109 journeys/week as a driver 8.5

Percentage of... work as driver 10social purposes 42

shopping/services/domestic 35

As table 3.2 shows, addressing other modes of transport respondents had used in the

last month, most people had never used the train, a motorbike or bicycle as a

(alternative or additional) mode of transport. On average people are slightly more

likely to use the bus once a month. By far the most popular other mode of transport

was walking 36% of the sample said they walk more than half a mile everyday, with

almost a quarter of people doing this two or three times a week. This compares

favourably to the national picture, where only 26% of the UK population over 65 years

walk daily and 44% never walk (ONS, 2004, 2006).

Table 3.2: Percentage of participants responding to frequency of other mode oftransportNever Once

amonth

Once afortnight

Once aweek

2/3times aweek

Daily Total%

Train 75 17 4 4 0 0 100Bus 58 21 8.5 8.5 4 0 100Motorbike/moped 91 0 0 0 4.5 4.5 100Cycle 87 4.3 0 8.7 0 0 100Walk 24 8 0 8 24 36 100


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3.1.2 Procedure

Participants took part in four stages of research an interview and a driver diary were

flanked by two waves of focus groups. At the end of the first focus group each

participant completed a background details questionnaire. Between focus group

meeting one and meeting two (a period of about one month) participants completed a

driver diary (around four weeks worth of driving) and took part in a telephone

interview (1-2 weeks after the initial focus group) lasting for about 20-25 minutes.

Participants formed three separate focus groups, based on proximity to where they

lived - group 1 met in Dorchester (seven individuals), group 2 in Hamworthy (close to

Poole) (seven individuals) and group 3 in Swanage (twelve individuals). Table 3 shows

how many people took part in each of the stages of data collection during this

research. As can be seen the drop-out rate across all of the stages amongst all groups

was low.

Table 3.3: Number and percentage of participants taking part in each stage of theresearch

Focus Group 1n(%)

Interviewn(%)

Focus Group 2n(%)

Driver Diaryn(%)

Hamworthy 7 (100%) 6 (85.7%) 7 (100%) 6 (85.7%)Dorchester 7 (100%) 3 (42.9%) 6 (85.7%) 5 (71.4%)

Swanage 12 (100%) 10 (83.3%) 11 (91.7%) 11 (91.7%)Total 26 (100%) 19 (73.1%) 24 (92.3%) 22 (88.5%)

(i) Focus Groups

All of the focus groups lasted for 1 hours and were conducted in the daytime or

early evening with refreshments provided. The three groups convened in locations

with easy access. The venues included a function room in an older peoples

organisation (Dorchester), a function room in an older peoples home (Swanage) and a

hall in an older peoples residential complex (Hamworthy). All rooms were private,

quiet and free from interruption in order to facilitate discussion. They were recorded

using a digital Dictaphone.

Wave one of the focus group was semi-structured, so that the needs and issues raised

came from the participants themselves. Driving experience was discussed including

journeys made, number of journeys by car, number of journeys by other modes,

reason for choice of mode, main barriers faced while driving and how such barriers are


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collecting cards on specific types of driving issue (these were previously discussed in

the earlier stages of data collection). As cards appeared a discussion on the issue

named on the card took place. The board-game approach to the focus group allowed

topics to appear in a random-order, reducing order-effect bias, and the friendly yet

competitive spirit enhanced conversation and directed focus, resulting in an increased

amount and depth of discussion. Across the three groups a total of 24 individuals

(92.3%) attended wave 2 focus groups

Figure 3.2. Board-game used in Phase 1, Wave 2 focus groups

(ii) Telephone Interviews

Nineteen (74%) of the initial 26 participants were interviewed over the telephone at a

mutually convenient time by an experienced researcher (the other participants were

unavailable when called). The telephone was chosen to keep participants at their ease

and not to take up too much time and effort on their part. The interviews were semi-

structured and involved re-visiting travel and driving needs from wave 1 focus groups

and assessed barriers to meeting such needs. In addition, the interview allowed

researchers to explore the findings from wave 1 and look for individual and personal

views and similarities and differences on the findings.

(iii) Driver diaries

A total of 22 (87%) participants completed a driver diary. The aim of the diary was to

get drivers to record their driving, mobility and travel needs as they occurred, rather

than retrospectively as would happen in the interviews and focus groups. The diaries


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were given out at the first focus group and collected in at the second focus group and

were discussed during the telephone interview. Individuals had a proforma to keep

details of any journeys made by car (date, number of miles, number of passengers,

destination etc) and the purpose for the journey and record anything unusual that

happened and any particular issues or problems that arose. They were asked to keep

the diary and record details for as long as they liked. They were kept on average for

19 days and covered 8.2 journeys (many of them return journeys) with an average

mileage of 240.7 miles (an average of 29 miles per journey or 88.7 miles per week).

3.1.3. Ensuring Validity and Trustworthiness of the Research

Checks of integrity, trustworthiness, validity and consistency were ensured during data

collection and analysis. Triangulation and reflexivity were explored in order to

investigate similarities and explore differences amongst the data analysis. The study

used four different methods to collect data on travel and driver needs two waves of

focus groups, an interview and a driver diary. Each method was checked for consistent

themes during analysis. The iterative nature of these data collection techniques

allowed areas of disparity or contention to be tackled with the participants during

interviews and the latter focus group. Two researchers were involved in this research

both making notes (using reflexive case notes) and analysing data which were

compared and discussed for consistency and contention. Areas of consistency were

reported and areas of contention were discussed and debated amongst the researchers

until a decision was made over their validity of inclusion in the write-up.

3.1.4. Data Analysis

Since the research involved an emergent and iterative design, data analysis ran

concurrently with data collection. Initially the data was transcribed exactly. Alongside

this researcher notes and reflexivity were analysed. A thematic analysis was adopted

to codify the answers. This involved initially analysing the transcription in light of the

reflexive processes. A thematic analysis was employed to break-down and re-build the

data using a process of Constant Comparative Analysis (Glaser, 2001; Goetz and

LeCompte, 1981; Janesick, 1994; Lincoln and Gruba, 1985). This produced a summary

of the data which was further reduced through a process of detection of units of

meaning into areas of general, relevant and essential distinction. The summarised

data is then addressed for patterns or connections within the data. Further data


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analysis occurred at the end of the data collection to supplement the process in light

of new findings. Finally, independent analysis took place to establish investigator

triangulation to enhance validity.

3.2. Phase Two Methodology

3.2.1 Participants

The sample of participants at phase two consisted of 31 individuals (18 males and 13

females), with ages ranging from 65 to 92 years old (mean = 76 years old, SD = 4.3).

As in phase one, recruitment took place by approaching people in town centres in

well-lit areas in the middle of the day, by professional recruiters and through help ofcharities addressing older people issues including Age Concern and Help the Aged.

Potential participants were given information sheets explaining the project and how

they can get involved and inline with ethical codes of conduct three main areas were

highlighted to them: informed consent (a letter to all participants and was distributed

at the recruitment stage and re-emphasised at the start of each focus group and

telephone interview), protecting the participants (the right to withdraw themselves,

any information or answers given at any time is allowed and this included after the

focus groups) and anonymity and confidentiality (transcripts of the focus groupswritten by the research team are anonymous). Participants were not paid and were

happy to volunteer their opinions, attitudes and tell their story for no reimbursement.

Participants were recruited from urban, semi-urban and rural areas of Dorset, Devon

and Cornwall, three largely rural counties with a high proportion of older people,

found in the South of England. All of the participants had given-up driving between 18

months and 6 months prior to the interview (mean age of giving up driving = 74 years

old, SD 4.5). Table 3.4 shows the average amount and type of driving carried out bythe participants in the year prior to giving-up driving. On average, participants drove

91 miles per week prior to giving-up driving, ranging from 15 to 200 miles. This

compares favourably to the national statistics on driving in the UK; older drivers (aged

65 and over) drive around 102 miles per week on average (DfT, 2006a). Average

number of journeys per participant per week was reported at around 7.6. People in

this sample used their car most for social purposes the average response was 38%. The

average percentage given to services was 37%. The average for work purposes was 8%,


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for other (responses included things such as sightseeing and pleasure) purposes the

average percent was 17%. This reiterates the notion that driving for older people is

crucial for social activities and amenities.

Table 3.4: Driving statistics for the participants in the year prior to giving up drivingParticipant Mean

AverageNumber of

..miles driven/week 91 journeys/week as a driver 7.6

Percentage of journeys for... work purposes 7social purposes 38

shopping/services/domestic 37

3.2.2 Procedure

Phase 2 involved an in-depth telephone interview which included participants verbally

completing the background details questionnaire found at phase 1. Interviews lasted

between 45 minutes and 1 hour 30 minutes and took place at a mutually convenient

time for the participant and researcher. The interview was designed to cover four

objectives (see appendix G for interview schedule):

To assess at what age people give-up driving;

To address the motivation for people giving-up driving;

To address changes in (travel) behaviour when people give-up driving,

especially addressing practical, social and aesthetic issues;

To discuss what might help older people prolong safe driving, with specific

reference to the role of technology.

3.2.3 Ensuring Validity and Trustworthiness of the Research

As with phase one, checks of integrity, trustworthiness, validity and consistency were

again ensured during data collection and analysis. The researcher was reflexive

throughout the interview, transcription and analysis. Findings were discussed with

other researchers to help ascertain meanings and contextualise findings.

3.2.4 Data Analysis

Initially the data was transcribed exactly. Researcher notes and reflexivity were then

added to the transcription. Again a thematic analysis was adopted to codify the


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information distributed in phase 1 and inline with Banister et al. (1994) all participants

were subject to the same level of protection as those in phase 1 and

In total 18 participants actively took part in the discussion. They are grouped in the

following categories (names are either first names or pseudonyms were given!):

- There were 6 academics or researchers interested in older peoples driving

and/or travel needs

o Asterix

o Marie

o Milette

o Natasha

o Mater

o Alex

- There are 4 older people who took part in earlier rounds of the project

o DennisM

o DennisB

o Peter

o Christopher

- There are 4 technology experts interested in designing in-vehicle control and

safety systems

o Anthony

o Steed

o Benjamin

o Greaser

- There are 4 car or car component designers and technologists interested in

human factors

o Arnd

o Alan

o Emily

o Bink


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3.3.3 Procedure

Technologies were presented to a panel of experts for their judgments to be recorded

in terms of likelihood, desirability, feasibility and cost effectiveness of each proposed

technology if it were adopted. The procedure involved three rounds of in-depth

discussion (exact format of questions can be found in appendix H):

Round 1 Vignettes and scenarios featuring top 4 technologies as proposed

during phase 1 and 2, which were as follows:

o Displaying road speed in the vehicle with additional speed cue

o In-vehicle Road Sign Display

o Night Vision

o Dazzle/glare reduction

Within each scenario, participants were asked to rate and discuss technology

on aspects such as:

o Likelihood of each proposed technology being adopted

o Desirability of each proposed technology

o Feasibility of each proposed technology

o Cost effectiveness of each proposed technology

Round 2 and 3 involved analysing and identifying any common agreement and

disagreement and re-submit a few discussion points for comment


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4. FINDINGS AND DISCUSSION:

TRAVEL NEEDS OF OLDER PEOPLE

4.1. Motivation for Travel Needs

The results from this study suggest older people are mobile and travel for a variety of

reasons including meeting appointments, going shopping and using services, social

purposes, work, helping others and for the journey itself. These seem to inhabit three

main categories:practical (primary) needs, social (secondary) needs and aesthetic

(tertiary) needs. As figure 4.1 shows their needs vary in level of self-awareness or

consciousness. Participants were very aware or conscious of primary needs and less

aware of secondary needs and even less aware of tertiary needs. The implication of

this is that interventions aimed at meeting mobility needs often only concentrate on

the most articulated primary needs. As will be discussed later, ignoring secondary and

tertiary needs has largely meant that such needs go unmet, particularly when private

travel modes have to be foregone. The categorisation of travel needs presented here

parallels with Maslows hierarchy of human needs (Maslow, 1970). Thus, the findings

suggest how important travel and mobility, and indeed the use of private vehicles, are

in achieving satisfaction and ultimately self-fulfilment.

PRIMARY MOBILITY NEEDSPRIMARY MOBILITY NEEDS

Practical NeedsPractical Needs

Make appointments, access shops and services, work,

SECONDARY MOBILITY NEEDSSECONDARY MOBILITY NEEDS

Social NeedsSocial Needs

The need for independence, control, status, roles.

TERTIARY MOBILITY NEEDSTERTIARY MOBILITY NEEDS

Aesthetic NeedsAesthetic Needs

The need for relaxation, visit nature, test cognitive skills

Mostawareness

Leastawareness

Figure 4.1 The three levels of mobility needs of older drivers by self-awareness of the

need


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4.1.1 Practical needs

It is important to consider the practical and utilitarian aspects of driving and the car

as aprimarymobility need. This includes fulfilling practical travel needs, such as

meeting appointments, visiting shops and services, visiting friends and attending social

events, going to work and helping others. It is these practical needs that have the

primary articulation i.e. when conceptualising travel and mobility these are thought of

and spoken about first.

In particular, the most important reason for travel amongst the participants was that

it helped them meet vital appointments, espec

mussel white haddad final report

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