data and experimental protocol from the experiments (d4.1) · deliverable no. 4.1 dissemination...

Deliverable No. 4.1 Dissemination Level (PU) Grant Agreement Number: 218496

ITERATE IT for Error Remediation And Trapping Emergencies

Data and experimental protocol from the

experiments (D4.1)

Deliverable No. D4.1

Workpackage No. WP4

Workpackage Title Experimental studies

Editor Björn Peters ([email protected])

Authors Björn Peters, Magnus Hjälmdahl (VTI), Frank Lai,

Anthony Horrobin (UNIVLEEDS), Simon Enjalbert

(UNIVAL), Carlo Cacciabue (KITE), and Ilit Oppenheim

(BGU)

Status First EC submission - Peer reviewed (nov 2011)

Reviewed and approved for submission 21/11/2011

EUROPEAN COMMISSION DG RESEARCH

A FP7 Collaborative Project Work programme: Sustainable Surface Transport SST.2007.4.1.2: Human physical and behavioural components


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The ITERATE project This report is produced within the European project ITERATE (IT for Error Remediation And

Trapping Emergencies), Grant agreement number 218496. The project started the 1st of January 2009

and will end 31st of December 2011.

The objective of ITERATE is to develop and validate a unified model of driver behaviour (UMD) and

driver interaction with innovative technologies in emergency situations. This model will be applicable

to and validated for all the surface transport modes. Drivers’ age, gender, education and experience

and culture (whether regional or company/organisational) are factors that will be considered together

with influences from the environment and the vehicle.

Such a unified model of driver behaviour will be of great use when designing innovative technologies

since it will allow for assessment and tuning of the systems in a safe and controllable environment

without actually putting them to use in real traffic. At the concept stage, the model could guide

designers in identifying potential problem areas whilst at the prototype stage, the model could inform

on the scenarios to be used in system evaluation. In this way the systems will be better adapted to the

drivers before being available on the market and will provide better support to the driver in emergency

situations. Along the same lines, the model could be of use for authorities as a guide in assessing and

approving innovative technologies without performing extensive simulator experiments or large scale

field trials.

ITERATE is based on the assumption that the underlying factors influencing human behaviour such as

age, gender, culture etc. are constant between transport modes. This assumption allows for a unified

model of driver behaviour, applicable to all surface transport modes, to be developed. This will be

done within ITERATE and the model can be used to improve design and safety assessment of

innovative technologies and make it possible to adapt these technologies to the abilities, needs, driving

style and capacity of the individual driver. The model will also provide a useful tool for authorities to

assess ITS which is missing today.

The project consortium consists of seven partners:

Statens väg och Transportforskningsinstitut (VTI) Sweden; University of Leeds (UNIVLEEDS) UK;

University of Valenciennes (UNIVAL) France; Kite Solutions s.n.c. (Kite) Italy; Ben Gurion

University (BGU) Israel; Chalmers University (Chalmers) Sweden; MTO Safety AB (MTOP) Sweden

For more information regarding the project please see http://www.iterate-project.eu/

I hope you will enjoy this and all other deliverables produced within the ITERATE project. If you seek

more information or have questions don’t hesitate to contact me.

Björn Peters, VTI Project coordinator e-mail: [email protected] tel: +46 13 20 40 00


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List of abbreviations

ACC Adaptive Cruise Control BSSS Brief Sensation Seeking Scale DAQ Driving Attitude Questionnaire DBQ Driver Behaviour Questionnaire ERTMS European Rail Traffic Management System ETCS European Train Control System FCW Forward Collision Warning FTP File Transfer Protocol ISA Intelligent Speed Adaptation ITERATE IT for Error Remediation And Trapping Emergencies KSS Karolinska Sleepiness Scale LKS Lane Keeping System PVT Psychomotor Vigilance Task RSME Rating Scale Mental Effort SSS Sensation Seeking Scale UMD Unified Model of Driver behaviour VAS Visual Analogue Scale VISIR VIsual SImulation for Road and rail


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Table of contents

Executive summary ............................................................................................................. vii

1. Introduction ................................................................................................................. 1

2. Pre-tests ........................................................................................................................ 1

2.1 Workload...................................................................................................................... 1

2.1.1 Purpose of the pilot ............................................................................................... 1

2.1.2 Experimental design ............................................................................................. 1

2.1.3 Results ................................................................................................................... 2

2.1.4 Conclusions ........................................................................................................... 3

2.2 Fatigue .......................................................................................................................... 4

2.2.1 Introduction ........................................................................................................... 4

2.2.2 Methodology ......................................................................................................... 4

2.2.3 Results ................................................................................................................... 5

2.2.4 Conclusions ........................................................................................................... 6

3. Main Experiments – Experimental Design ................................................................... 7

4. Driving task ................................................................................................................ 10

4.1.1 Car dive ............................................................................................................... 10

4.1.2 Train drive ........................................................................................................... 10

5. Workload manipulations ............................................................................................ 11

5.1.1 Car ....................................................................................................................... 11

5.1.2 Train .................................................................................................................... 12

6. Simulators .................................................................................................................. 13

6.1 Small scale portable simulators .......................................................................... 13

6.1.1 Complimentary hardware ................................................................................... 13

6.1.2 Car software ........................................................................................................ 13

6.1.3 Train software (VISIR) ....................................................................................... 13

6.1.4 Remote access and networking ........................................................................... 14

6.2 Stationary large scale simulators ........................................................................ 14

6.2.1 Large scale car simulator (LEEDS) .................................................................... 15

6.2.2 Large scale train simulator (VTI) ....................................................................... 15

7. Experimental Protocols .............................................................................................. 16

8. Data collected ............................................................................................................. 16

8.1 Overview ............................................................................................................. 16

8.2 Description of collected data .............................................................................. 17

8.2.1 Objective data: .................................................................................................... 18

8.2.2 Subjective data: ................................................................................................... 19

9. Additional information about the experiments ........................................................... 20

9.1 Logistics .............................................................................................................. 20

9.2 Recruitment of participants ................................................................................. 20

9.2.1 Comments ........................................................................................................... 21

9.3 Installation and setup of the portable simulators ................................................ 21

9.4 Running the experiment ...................................................................................... 21

9.5 Handling data ...................................................................................................... 22


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10. Use of data – rules of access ........................................................................................ 22

11. References .................................................................................................................. 23

12. Annex 1 Experimental Protocols ................................................................................ 24

12.1 Experimental procedure for Car drivers ............................................................. 24

12.1.1 Information about the car and systems (ISA and FCW) ..................................... 24

12.2 Experimental procedure for Train drivers ........................................................... 26

12.2.1 Information about the train, controller and display ............................................ 26

13. Annex 2 Web questionnaires ...................................................................................... 32

14. Annex 3 Hazard PercePtion test ................................................................................. 40

15. Annex 4 Informed consent Form ................................................................................ 43

16. Annex 5 Setting up the small scale PORTABLE SIMULATOR ................................. 44


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List of Figures Figure 1: The desktop simulator .............................................................................................................. 4

Figure 2: The experimental environment ................................................................................................ 5

Figure 3 A simple description of the experimental design; four between subject factors (sensation seeking, culture, experience and fatigue) and one within subject factor; workload (low, medium and high) ........................................................................................................................................................ 7

Figure 4 Rural road driving in the large scale car simulator at Leeds ................................................... 10

Figure 5 Map of the rail road track used in the experiment .................................................................. 11

Figure 6 The small scale portable simulator (to the left in car configuration and to the right in train configuration) ........................................................................................................................................ 13

Figure 7 The driver’s view (forward scene) in the train simulator ........................................................ 14

Figure 8 Large scale motion base car simulator at Leeds University .................................................... 15

Figure 9 Large scale (stationary) train simulator with a drivers desk ................................................... 16

Figure 10 Simulated train (Bombardier Regina) ................................................................................... 26

Figure 11 Train control for the portable train simulator ........................................................................ 27

Figure 12 Train control for the stationary train simulator (Bombardier Regina) .................................. 27

Figure 13 ETCS display in normal drive mode ..................................................................................... 27

Figure 14 ETCS display speed warning ................................................................................................ 28

Figure 15 ETCS display over speed warning ........................................................................................ 28

Figure 16 ETCS display new speed ahead ............................................................................................ 29

Figure 17 ETCS display new lower speed ............................................................................................ 29

Figure 18 ETCS display new speed and too late braking ...................................................................... 29

Figure 19 ETCS display new speed and too late braking warning ........................................................ 30

List of Tables Table 1 Latin square design of conditions ............................................................................................... 2

Table 2 Background data for participants ............................................................................................... 2

Table 3 Mean RSME scores for the 5 workload levels ........................................................................... 2

Table 4 Result of a pair-wise comparison ............................................................................................... 3

Table 5: Overview of participant characteristics ..................................................................................... 6

Table 6: Comparison of fatigue indicators before and after the experiment ........................................... 6

Table 7 Experimental design (car and train) 4 subjects per cell for each transport mode i.e. 160 car drivers + 160 train drivers (F = Female, M = Male) ............................................................................... 9

Table 8 Train workload control and duration ........................................................................................ 12

Table 9 Target number of subjects per test site and simulator .............................................................. 16

Table 10 Actual number of subjects per test site and simulator ............................................................ 17

Table 11 Description of variables in car driving data files (same format for FCW and ISA) ............... 18

Table 12 Description of variables in driving data files (same format for FCW and ISA) .................... 19

Table 13 Distribution of car drivers with respect to country, gender, experience, and driver state. ..... 20

Table 14 Distribution of train drivers with respect to country, gender, experience, and driver state .... 21

Table 15 Time table for the experimental drive .................................................................................... 30


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EXECUTIVE SUMMARY

The aim of this deliverable is to describe the experiments performed in WP4. The actual planning of the experiments was done in WP3 and described in Deliverable 3.1 (Barnard, Lai et al., 2010b). However, there were some deviations from the original plan as part of the actual execution of the experiments which is what is described in this deliverable. Thus, this deliverable provides essential information for the interpretation and further use of WP4 data. It can be considered as a manual to WP4 data. Furthermore, some additional information which is considered useful was also included. The results (analysis of data) from the WP4 experiments are reported in Deliverable 5.1 (Tapani, Forsman et al., 2011) and also provide a key to the interpretation of the data. Data will be further explored by the project partners after the project end in December 2011. However, after the end of 2013, data will be made available to the research community for further use. Those interested should contact the project coordinator for further information.


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1. INTRODUCTION

In total 12 experiments with a common design was conducted in WP4. The experiments were performed in 5 countries with help of 2 identical portable simulator platforms and 2 large scale (non-portable) simulators. Six of the experiments were done with professional train drivers and six with passenger car drivers. Two pre-tests were done prior to execution of the experiments in order to determine how to manipulate two of the experimental factors.

2. PRE-TESTS

Two pre-tests were conducted in order determine the workload and fatigue manipulations to be used in the experiments. The pre-tests was done in line with the experimental outline described in Deliverable 3.1 (Barnard, Lai, et al., 2010b)

2.1 WORKLOAD

The first pre-test focused on workload manipulation.

2.1.1 Purpose of the pilot

To confirm that operators indeed experience distinct levels of workload by the experimental design

2.1.2 Experimental design

The manipulation of workload levels was initially envisaged in WP3 as:

• Low workload: driving on a stretch of road with very gentle curves • Medium workload: driving on a stretch of road with curves which are a bit curvier than those

on the low workload road • High workload: driving on the medium workload road and carrying out a serial subtraction

task of counting backwards in steps of sevens One of the objectives in WP3 was to make the car and the train experiments as comparable with each other as possible. After the prototype of the train track became available, preliminary tests at VTI suggested that there seemed to be no difference in the perceived difficulty between driving on the low and medium workload sections of the track. It was therefore decided to include counting backwards in steps of 1 and 3 in addition to 7, with a view of including secondary task as part of the medium workload manipulation. The levels of workload manipulation tested were:

• Level 1: driving on the A2 Road which is a stretch of road with very gentle curves (15⁰ angles) throughout.

• Level 2: driving on the A1 Road which a stretch of road with curves which are a bit curvier (30⁰ angles) than those in A2.

• Level 3: driving on the A1 Road and counting backwards in 1 • Level 4: driving on the A1 Road and counting backwards in 3 • Level 5: driving on the A1 Road and counting backwards in 7

Participants’ perceived workload was measured by RSME (Rating Scale Mental Effort; Zijstra, 1993). Where the counting-backward task was included, correctness was also monitored.


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The sequence of drives per participant was counterbalanced to minimise the learning effect. A full counterbalance of 5 levels requires 120 combinations of sequences, which was not deemed to be feasible due to constraints in resources. A partial counterbalanced design was developed using the Latin Square (see Table 1).

Table 1 Latin square design of conditions

Run1 Run2 Run3 Run4 Run5

sub01 1 3 5 2 4

sub02 2 4 1 3 5

sub03 3 5 2 4 1

sub04 4 1 3 5 2

sub05 5 2 4 1 3

sub06 4 2 5 3 1

sub07 5 3 1 4 2

sub08 1 4 2 5 3

sub09 2 5 3 1 4

sub10 3 1 4 2 5

2.1.3 Results

20 participants were recruited for the test. Background data can be found in Table 2.

Table 2 Background data for participants

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Age (years) 20 21 61 31.95 11.532

Mileage (miles) 20 100 12000 6180.00 3834.827

Experience (years) 20 1 45 13.30 11.258

. The mean RSME scores can be seen in Table 3.

Table 3 Mean RSME scores for the 5 workload levels

Descriptive Statistics

Mean Std. Deviation N

L1 21.80 12.155 20

L2 26.05 17.352 20

L3 47.15 18.936 20

L4 64.40 18.190 20

L5 78.50 20.046 20

(L = Level)


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There was a main effect F(4,76) = 101.77, p < 0.0005, ES = 0.84 of workload. Indicating that the counting task provided increase in workload as expected.

Table 4 Result of a pair-wise comparison

Pairwise Comparisons

(I)

worklo

ad

(J)

worklo

ad

Mean

Difference (I-

J) Std. Error Sig.a

95% Confidence Interval for

Differencea

Lower Bound Upper Bound

1 2 -4.250 2.363 .880 -11.749 3.249

3 -25.350* 3.457 .000 -36.323 -14.377

4 -42.600* 3.439 .000 -53.515 -31.685

5 -56.700* 3.865 .000 -68.966 -44.434

2 1 4.250 2.363 .880 -3.249 11.749

3 -21.100* 4.327 .001 -34.834 -7.366

4 -38.350* 3.687 .000 -50.050 -26.650

5 -52.450* 3.864 .000 -64.713 -40.187

3 1 25.350* 3.457 .000 14.377 36.323

2 21.100* 4.327 .001 7.366 34.834

4 -17.250* 2.864 .000 -26.341 -8.159

5 -31.350* 3.296 .000 -41.811 -20.889

4 1 42.600* 3.439 .000 31.685 53.515

2 38.350* 3.687 .000 26.650 50.050

3 17.250* 2.864 .000 8.159 26.341

5 -14.100* 2.384 .000 -21.666 -6.534

5 1 56.700* 3.865 .000 44.434 68.966

2 52.450* 3.864 .000 40.187 64.713

3 31.350* 3.296 .000 20.889 41.811

4 14.100* 2.384 .000 6.534 21.666

Based on estimated marginal means a. Adjustment for multiple comparisons: Bonferroni. No statistical difference between L1 and L2. Of the 20 participants:

• 7 rated L1 being more difficult than L2 • 2 didn’t differentiate the two levels

The results were not affected by age, mileage, or experience.

2.1.4 Conclusions

The differences in road geometry alone did not seem to be sufficient for imposing distinguishable perceived workload. It therefore appears to be a sensible solution by introducing secondary task into manipulation of the medium workload. Participants felt that they had to try harder to complete counting backwards in 7 than in 3, the objective performance between the two was not statistically different. Although this could be


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attributable to the sample size, it does imply that the differences between counting backwards in 1 and 7 would be more prominent. Hence, the recommended workload manipulations were in view of the forthcoming experiments:

• Low workload: driving alone (i.e. Level 1 in this pilot experiment) • Medium workload: driving + counting backwards in 1 (i.e. Level 3 in this pilot experiment) • High workload: driving + counting backwards in 7 (i.e. Level 5 in this pilot experiment)

2.2 FATIGUE

The second pre-test focused on fatigue manipulation.

2.2.1 Introduction

Within the ITERATE WP4 experiment, task-induced fatigue was proposed to impose on half of the participants. WP3 recommended recruiting a group of participants who would take the experiment after lunch and further ensuring their fatigue by asking them to carry out an observation task of 25 minutes in order to achieve task-induced fatigue prior to the actual driving task. This pilot experiment aimed to verify such a manipulation.

2.2.2 Methodology

A desktop simulator (Figure 1) was used for this pre-test. The road was a stretch of three-lane motorway with fairly low traffic. The host vehicle was equipped with an automated driving system consisting of Adaptive Cruise Control (ACC) system with Stop-and-Go functionality and a Lane Keeping System (LKS). When this automated driving system was activated, it kept a pre-set headway from the lead vehicle, as well as keeping the vehicle in the centre of the lane.

Figure 1: The desktop simulator

Participants’ level of fatigue was measured both subjectively and objectively:

• The Karolinska Sleepiness Scale (KSS): a nine-point scale ranging from ‘Extremely alert’ (1) to ‘very sleepy, great effort to keep awake, fighting sleep” (9) (Gillberg et al., 1994; Reyner & Horne, 1997).


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• Visual Analogue Scale (VAS): a 100mm bi-polar scale with the left end representing ‘very alert’ and the right end representing ‘very sleepy’ (Hayes and Peterson, 1921 and Freyd, 1923)

• Psychomotor Vigilance Task (PVT) (Wilkinson and Houghton, 1982): a reaction task during which participants are asked to respond as quickly as possible to a visual stimulus. In this study, it was a number shown on the centre of the PC monitor at a random interval between 2,000 and 10,000 ms. Participant fatigue was indicated by reaction time as well as missed responses, defined as any response over 500 ms.

Nine drivers holding a valid UK driving licence participated in this study. Participants were recruited locally without consideration of demographic factors. They were asked to have lunch before attending the experiment and asked to refrain from consuming drinks containing caffeine during and post lunch. The experiment slots were accommodated to individuals’ lunch time; all participants completed the experiment between 13:00 and 15:30. During the experiment, the room lighting was switched off to create a dimmed environment (Figure 2).

Figure 2: The experimental environment

A briefing on the experiment was provided to the participants upon arrival, followed by an invitation to ask questions. Once the participants’ consent was acquired, they were asked to complete the KSS, VAS, and PVT. This was followed by the experiment, setting off the vehicle from a slip road, and merging onto the motorway. The participant was in full control of the vehicle’s manoeuvre during the first mile. The automated driving system was activated upon the vehicle passing the first junction, from which point the participant’s task became monitoring and lasted for 25 minutes. At the end of the 25 minutes, the experimenter approached the participant, terminated the experiment, and switched the light back on. The drive was followed by completing the KSS, VAS, and PVT again.

2.2.3 Results

Of the nine participants, four were female and five were male. Table 5 depicts the participants’ characteristics.


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Table 5: Overview of participant characteristics

Mean SD Max Min

Age 35.33 6.02 47 29 Annual mileage (km) 13,947 5,858 24,140 6,437 Experience (number of years

since obtained driving licence) 16.00 6.22 27 6

Table 6 shows that subjective measures provided strong evidence of the 25-minute monitoring task making the participants become more fatigued. Objective measures demonstrated the trend in the expected direction, although the difference was not statistically significant, which is thought to have resulted from a combination of small sample and effect size.

Table 6: Comparison of fatigue indicators before and after the experiment (ES = Effect Size)

Mean RM ANOVA

Before After F p ES

KSS (1-9) 4.33 5.83 F(1,8)=9.00 0.017 0.53

VAS (0-100) 37.28 52.50 F(1,8)=5.37 0.049 0.40

PVT reaction time (seconds) 0.30 0.31 F(1,8)=0.51 0.497 0.06

PVT miss rate (%) 0.56 1.11 F(1,8)=0.31 0.594 0.04

It is worth mentioning that the rate of changes in the aforementioned fatigue indicators did not correlate with any of the driver characteristics, which suggests that the effect of the proposed monitoring task on increased fatigue is independent of age, annual mileage, and experience.

2.2.4 Conclusions

The results from this pre-test demonstrate that the participants were already somewhat fatigued and that the proposed 25 minutes of monitoring task carried out after lunch in a dimmed environment is a valid manipulation for further ensuring their fatigue.


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3. MAIN EXPERIMENTS – EXPERIMENTAL DESIGN

The experimental design used in WP4 was developed in WP3 (Barnard, Lai et al., 2010b). and is depicted in a simple form in Figure 3. This deliverable will provide information about the actual conduct of the experiments. A mixed design with four between factors and one within factor was applied. Sensation seeking (as measured by the Brief Sensation Seeking Scale (BSSS) (Hoyle et al. 2002)) was not actually controlled for by screening subjects but rather by forming groups of drivers based on collected BSSS scores. The same applied for culture which was measured by the Traffic Culture and Climate Scale developed by Özkan et al. (2006) with 44 items related to traffic culture as an indicator of culture, country of living. Experience determined by the number of years as a train driver or the number of years holding a car driving license for train and car drivers respectively. Experience was a factor with two levels (novice and experienced) determined by the number of years as a train driver or the number of years holding a car driving license. Fatigue was manipulated by scheduling subject before or after lunch and by exposing the fatigue drivers to a boring “drive” (i.e. watching a 25 minutes long video clip from a simulated motorway drive, see also chapter 2.2.2 above). The assumption was that after lunch dip and boring task would induce slightly increased level of sleepiness. No shift workers were included and all subjects should have had a normal night’s sleep before the participation. Sleepiness was measured with help of the Karolinska Sleepiness Scale (KSS) developed by Gillberg et al. (1994) and modified by Reyner & Horne (1997). See also the workload pre-test in chapter 1. Workload was manipulated by a secondary task (backwards counting in steps of 1 or 7), resulting in three workload levels (low, medium and high).

Figure 3 A simple description of the experimental design; four between subject factors

(sensation seeking, culture, experience and fatigue) and one within subject factor; workload

(low, medium and high)

The subjects were also asked to complete Sagberg’s and Bjørnskau’s Hazard Perception Test (HPT) (Sagberg and Bjørnskau, 2006) that could be used to verify the relationship between experience and hazard perception skills.

workload

fatigue

workload

culture

workload

sensation seeking

workload

experience


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A more elaborated view of the experimental design is shown Table 7. The objective was to have 160 car drivers and 160 train drivers with an equal gender, fatigue and experience distribution for the experiments with the portable simulators. Furthermore, 32 + 32 participates were planned for the validation large scale stationary experiments (train and car). Thus the total target was 382 participants. However, this target was not possible to reach for several reasons which are discussed in chapter 8 and 9.


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Table 7 Experimental design (car and train) 4 subjects per cell for each transport mode i.e. 160 car drivers + 160 train drivers (F = Female, M =

Male)

Between subject

France Great Britain Israel Italy Sweden

Fatigue Alert Fatigue Alert Fatigue Alert Fatigue Alert Fatigue Alert

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

Experienced

Novice

F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M

Within subject

High

workload

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

Medium

workload

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

Low

workload

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4


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4. DRIVING TASK

The driving tasks plans are described in Deliverable 3.1 (Barnard, Lai et al., 2010b).. However, there were some minor deviations from the plan. Thus, brief descriptions and actual tasks used in the experiments are provided here to facilitate the use of WP4 data. All subjects were given written instructions about the driving task (car and train) prior to the drive. Furthermore, they made a training drive before the actual test drive.

4.1.1 Car dive

The car driving task was divided in two parts, driving on a two-lane rural road (Figure 4) with an Intelligent Speed Adaptation System (ISA) and motorway driving with a Forward Collision Warning System (FCW). The ISA part of the car experiment included negotiating speed limit changes and sharp curves, as well as driving through villages and a school zone. In the FCW condition, the driver encountered events with a lane changing truck, a road work with a lane drop, the sudden braking of a car in front and breakdown of a downstream vehicle.

Figure 4 Rural road driving in the large scale car simulator at Leeds

4.1.2 Train drive

The train driving task had lasted approx. 85 minutes with 11 stations and the actual geometry of the track was based on real data from Sweden (see Figure 5). The drive started in Falköping and ended in Nässjö. Station names were changed to sound more international (see Table 8 and 12.2.1). More details can also be found in Deliverable 3.1.


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Figure 5 Map of the rail road track used in the experiment

The driving task was more or less a speed keeping task, keeping the time table and stopping at the stations.

5. WORKLOAD MANIPULATIONS

Workload was manipulated by a backwards counting task with two levels. Medium workload was achieved by asking the subjects to count backwards in increments of “1” and tell the numbers so that the test leader could hear. During High workload backwards counting was done with steps of “7”. The task was initiated and terminated by an artificial voice giving instructions to the subjects. The voice was controlled by the simulator software and messages were translated into Swedish, French, Italian and Hebrew. The counting tasks were included in the training preceding the experimental drive both for car and train.

5.1.1 Car

During the experimental car drive there were 2 low, 2 medium and 2 high workload situations according to the experimental specification in Deliverable 3.1 (Barnard & Lai, 2010b). The conditions were divided between ISA and LCW drives so that there were one of each workload condition per drive (see Fel! Hittar inte referenskälla. and Fel! Hittar inte referenskälla.). Start and stop was controlled based on distance driven.


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5.1.2 Train

During the experimental drive there were 2 medium and 2 high workload situations according to the experimental specification in Deliverable 3.1. The medium lasted for approx. 15 minutes and the high for 5 minutes. In between there were sections with low workload with an approx. duration of 5 minutes. However, start and stop was controlled based on distance driven (see Table 8).

Table 8 Train workload control and duration

Station Distance (km + m) Time h:m:s Workload

Alpha 0 12:00:00 Low (no counting) 9+501 Start Medium (ca. 15 min) Bjorn 10+776 12:06:00 Medium Charlie 25+271 12:13:00 Medium 36+001 Stop Medium 36+002 Low Davidtown 37+032 12:21:00 Low 38+565 12:26:00 Low 46+001 Start High (ca. 5 min) Ertico 49+746 12:29:30 High 50+838 12:31:00 High 56+500 End High 56+501 Low 57+001 Start Medium (ca. 15 min) Franktown 58+060 12:36:00 Medium Golden 68+337 12:43:30 Medium 71+136 12:46:00 Medium Habo 75+390 12:49:00 Medium 77+001 Stop Medium 77+002 Low Jamboree 95+967 01:05:00 Low 102+001 Start High (ca 5 min) Kitewille 103+050 01:10:00 High 109+001 End High 109+002 Low Lulu 110+660 01:14:00 Low


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6. SIMULATORS

Two identical small scale portable simulators were built by VTI and Leeds. The basis for this approach is described in Deliverable 3.1 (Chapter 6). This chapter provides only additional information which is not included in Deliverable 3.1.

6.1 Small scale portable simulators

The two portable simulators were built in close collaboration between VTI and Leeds (Figure 6). Two wooden boxes were built by VTI and used for the transportation of the simulators between the partners.

Figure 6 The small scale portable simulator (to the left in car configuration and to the right in

train configuration) (with permission)

6.1.1 Complimentary hardware

The following complimentary equipment was bought for the simulators; a sound system by Logitech Z2300, extra hard disk for back up, power cords, wireless internet modem, and 2 lamps (3 * 60W).

6.1.2 Car software

The software (UoLDS) is based on OpenSceneGraph version 2.8.3, compiled on Visual Studio 2005 (Windows) or gcc (Linux). The code is written in C++ with lua (www.lua.org) for scripting of scenarios and configuration files and SWIG (www.swig.org) to generate bindings between the two languages. The visual database is modelled using Presagis Creator ( www.presagis.com ). The software can be deployed in a cluster environment with projectors, a single desktop or laptop, with single or multiple monitors. Configuration files are used to describe the projection setup, scenario and visual database. The ITERATE simulator used a Logitech G27 steering wheel with force feedback. The vehicle model used an automatic gearbox so the gear-shifter was not required.

6.1.3 Train software (VISIR)

The VISIR (VIsual SImulation of Road/Rail) 3d graphics simulation package was designed by VTI for use in different types of research- and training simulators in a road or rail environment, where one or several displays are used to present the scene for a driver.


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VISIR uses OpenSceneGraph (OSG) graphical engine version 2.8.3 (www.openscenegraph.org) and the boost library 1.35.0 (www.boost.org). All code is written with object oriented methods in C++ using Visual Studio 2008 (Windows) and GCC (Linux). VISIR has been influenced by earlier in-house developed graphical packages and experiences of simulators since 30 years. It has also been influenced by a previous development project which was developing a software package for rail simulation, SST. VISIR presents dynamic views of the database including present status of all participating actors, as they have been defined via a network connection from an external computer. Alternatively, the system can be used in laptop-mode, where all controls are handled by a single computer. VISIR generates a complete virtual presentation of the world as seen from a viewer`s perspective. Even if the viewer normally is represented by the driver, other viewer positions in the environment are also possible. The viewer is always connected to an actor e.g. a vehicle, a train, a helicopter or other. Moving the viewer is accomplished by moving the connected actor. The database is configurable via a set of configuration files. The view from the driver’s seat is shown in Figure 7.

Figure 7 The driver’s view (forward scene) in the train simulator

6.1.4 Remote access and networking

A software tool called LogMeIn® was used by Leeds and VTI to get remote access to the simulators for uploading software changes when needed. This worked quite fine and even a wireless internet connection could be used for this purpose. Once an experiment was completed data were uploaded a dedicated ftp site at VTI. As data files were quite large it was sometimes difficult to upload data if there was only a slow speed internet connection available.

6.2 Stationary large scale simulators

Two stationary large scale simulators were used in a second phase of WP4 experiments.


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6.2.1 Large scale car simulator (LEEDS)

The simulator is based on a Jaguar S-type cab which is housed within a 4m diameter, composite, spherical projection dome (Fel! Hittar inte referenskälla.) The vehicle's internal Control Area Network (CAN) is used to transmit driver control information between the cab and the network of PCs that manage the overall simulation. The driver can feel accurate loading at all the normal controls, including the steering wheel and brake pedal. Inside the cab, all of the inherent dashboard instrumentation functions normally. A real-time, fully textured 3-D graphical scene of the virtual world is projected on the inner surface of the dome. The projection system consists of five forward and three rear channels. The forward channels are edge-blended to provide a near seamless total horizontal field of view of 250°. The vertical field of view is 45°. The central rear channel (60°) is viewed through the vehicle's rear view mirror, whilst LCD panels are built into the Jaguar's wing mirrors to provide the two additional rear views. The display resolution of all channels is 4.1 arcmin per pixel. This imagery is generated by five dedicated PCs, housing nVidia FX3000G and nVidia FX4500G graphics cards. The eight visual channels are presented at 60 frames per second and at a resolution of 1024x768 (800x450 for the two wing mirror displays). The PCs are frame-locked to avoid any “tearing” of the visual image.

Figure 8 Large scale motion base car simulator at Leeds University

6.2.2 Large scale train simulator (VTI)

The large scale train simulator used in the project was built by VTI. It consists of a train mock-up with a driver’s desk which resembles what can be found in a Bombardier Regina train which are common in Sweden (Figure 9). The front view was shown on a large LCD screen (similar to what was used in the portable simulators) and a smaller screen was used for the ETCS display. The train control for speed and brake was identical to what is used in the Bombardier Regina trains. See Annex 1 for further details. Furthermore, there was a dead man’s control pedal which the drivers had to keep halfway pressed down while driving. The cabin can be placed on a motion platform to provide lateral and longitudinal motion feedback, the same as used for the advanced car simulators at VTI. However, this was not done in the present experiment as it was not considered necessary


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Figure 9 Large scale (stationary) train simulator with a drivers desk (with permission from

participant)

The preparation of the simulator was a bit tedious as we had to install the new real train control from Bombardier and a small screen for the ETCS display.

7. EXPERIMENTAL PROTOCOLS

The experimental procedures which were common to all experimental sites and the instructions to the participants can be found in Annex 1.

8. DATA COLLECTED

This chapter describes the data collected in the WP4 experiments. Additional information can also be found in the annexes.

8.1 Overview

Twelve experiments were conducted in WP4 at six test sites by five partners in five different countries. Three types of simulators were used in the experiments; a small scale portable simulator and two more advanced stationary simulators. The ambition was to collect data from 384 subjects (Table 9). However, the final database contains 293 entries (76 % of target for car and train), see Table 10. The lack of data relates mainly to train drivers. See also chapter 9 for more information. All data was uploaded to a FTP site located at VTI and described in the following.

Table 9 Target number of subjects per test site and simulator

WP4 WP4 WP4 WP4 Total

Mobile car simulator

Mobil train simulator

Stationary car simulator

Stationary train simulator

France 32 32 96

Great Britain 32 32 32 96

Israel 32 32 64

Italy 32 32 64

Sweden 32 32 32 64

Total 160 160 32 32 384


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Table 10 Actual number of subjects per test site and simulator

WP4 WP4 WP4 WP4 Total

Mobile car simulator

Mobil train simulator

Stationary car simulator

Stationary train simulator

France 32 6 38

Great Britain 30 19 29 78

Israel 31 14 45

Italy 27 18 45

Sweden 34 21 32 87

Total 154 78 29 32 293

8.2 Description of collected data

Both objective (simulator data) and subjective data were collected during the experiments. All data is stored on a FTP site at VTI. With the following folder structure (in parenthesis content information):

• # WP4 Data

o Info and Overview (coding of subjects – excel file)

o Objective data (text files)

� Car

• Advanced Simulator

o GB

• Mobile simulator

o FR

o GB

o IL

o IT

o SE

� Train

• Advanced Simulator

o SE

• Mobile Simulator

o FR

o GB

o IL

o IT

o SE

o Subjective data (excel and SPSS files)


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8.2.1 Objective data:

All objective data (driving data) on the FTP is in ASCII format. A short description of the data can be found here. Further details can be found in D5.1. Car driving: There are two files per driver (one for FCW condition and one for ISA condition) with 40 columns (variables) for car driving. The first row in each file provides labels for the 40 variables (see Table 11).

Table 11 Description of variables in car driving data files (same format for FCW and ISA)

Label Explanation

%TotalTime Time since Jan 1970 (s). SimTime Simulation Time (s). xyz.x subject car c.g. x (m). xyz.y subject car c.g. y (m). xyz.z subject car c.g. z (m). distanceJunc distance from the last junction (m). headway headway (s) This will be 999.999 if there is no leader. headway_distance Distance to leader (m) This will be 999.999 if there is no leader. Ttc Time to contact (s). This will be 999.999 if there is no leader. offset Offset from centreline of road (m). Left is negative. distance Distance along the current road segment (m). speed Speed of subject car (ms^-1). lane_index 0 for UK, 1 for Europe unless they cross the centreline. Acc throttle (0-100) %. Brk brake pedal effort (0-200) N. steering steering angle (degrees, clockwise positive ). major_road road identifier major. minor_road road identifier minor. road_type road type ( straight=1, curve=2 ). right_curve rightHand, ( right-handed road 1 = right, -1 = left ). leaderId leaderID, ID of lead car ( -1 for ISA ). front_left frontLeftOffset, offset of front left of car from centreline (m). front_right frontRightOffset, offset of front right of car from centreline (m). rear_left rearLeftOffset, offset of rear left of car from centreline (m). rear_right rearRightOffset, offset of rear right of car from centreline (m). left_edge leftEdge, offset of left edge of lane from centreline (m). right_edge rightEdge, offset of right edge of lane from centreline (m). collision collision flag, 1 = true. heading1 not used for ISA. heading2 not used for ISA. indicator not used for ISA. headlight not used for ISA. data tag not used for ISA. latacc lateral acceleration of subject car, ms^-2. longacc longitudinal acceleration of subject car, ms^-2. fcwWarningDistance fcwWarningDistance, (fcw warning distance, only when FCW is

active ie not in ISA). fcwWarningActive fcwWarningActive, (fcw warning flag, only when FCW is active

ie not in ISA ). swWarningActive swWarningActive, (speed warning flag ).


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swThreshold swThreshold, (speed warning threshold, ms^-1 ). swIsa swIsa, (isa enabled non-zero=true ). swBend swBend, (dashboard bend sign enabled, non-zero=true ). swSchool swSchool ( dashboard school sign enabled, non-zero=true ).

Train driving: There is one data file per diver. The first row provides labels for each data column (variable). A short description of the variables is given in Table 12.

Table 12 Description of variables in driving data files (same format for FCW and ISA)

Label Explanation

TestPerson Testperson ID localTime Local time on computer, ie. when the simulation was started

(YYMMDD HH:MM:SS) time simulationtime (seconds) scenarioClock Time in scenario (HH:MM:SS) throttle Applied throttle (0..1) brake Applied brake power (0..1) position Position on track (meters) permittedSpeed Permitted speed according to the ERMTS braking curve (km/h) distanceToTarget Distance to next ERTMS target (meters) targetSpeed Speed at next ERTMS target (km/h) sound If true ERTMS info sound is played (true/false) soundStart Started playing sound (name of sound) soundStop Stopped playing sound (name of sound) speed Current speed (m/s)

8.2.2 Subjective data:

The following subjective data was collected. Detailed information can be found in the annexes.

• KSS (Karolinska Sleepiness Scale) data

• Hazard Perception data (see Annex 3 for details)

• Questionnaire data from web-based questionnaires (See Annex 2 for details)

o Driving performance, realism and sickness – 5 questions

o Background data (demographics), sleep diary and experiences 9/11 questions

(car/train)

o Life style (Brief Sensation Seeking Scale) – 8 questions

o DBQ (Driving Behavior Questionnaire)

� Car – 12 questions

� Train (new) – 12 questions

o DAQ (Driving Attitude Questionnaire) car only – 20 questions

o Culture- 44 questions


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9. ADDITIONAL INFORMATION ABOUT THE EXPERIMENTS

This chapter provides some additional information about the actual execution of the WP4 experiments that could be of interest for the user of data.

9.1 Logistics

The two small scale portable simulators were shipped between the partners. The simulator built by ITS Leeds University was shipped after completion of their experiments to University of Valenciennes in France and after that to Ben Gurion University in Israel and finally back to ITS in Leeds, Great Britain. The second simulator built by VTI was first shipped to Italy for the HMAT conference in June/July 2010. It was successfully demonstrated at the conference and after the conference KITE started their experiments. In November 2010 it was shipped back to VTI’s office in Gothenburg, Sweden. It was decided to run the experiment in Gothenburg in order to get a better distribution of subjects and not do all the testing in Linköping where the experiment with the stationary train simulator had to run. However, a lot of problems were encountered with British simulator during its tour from England to France and further on to Israel and back to England. Problems were caused by customs regulations and carrier mishaps. Also insurance issues had to be solved.

9.2 Recruitment of participants

The recruitment of car drivers was much easier than finding train drivers (see below). The overall result was 98% of target for car drivers. The gender distribution was not ideal as there were only 45% female drivers. Furthermore, there were some problems finding novice drivers (less than 1 year of experience). The overall distribution was not too bad (59% experienced and 41% novices). However, there were quite few novices in Italy and Sweden. It was considered that the number of participants and distribution was sufficient for the analysis.

Table 13 Distribution of car drivers with respect to country, gender, experience, and driver

state.

Country Number Gender Experience State

Female Male Experienced Novice Alert Fatigue

France 32 7 25 16 16 16 16 Great Britain 30 15 15 16 14 15 15 Israel 31 16 15 16 15 16 15 Italy 27 11 16 20 7 16 11 Sweden 34 16 18 26 8 14 20 Total portable

simulator 154 65 89 94 60 77 77

Advanced simulator GB 29 17 12 15 14 14 15 Grand total 183 82 101 109 74 91 92

The overall result for train drivers was 57% of target. The French partners encountered the greatest problems recruiting drivers. But also the other partners had difficulties to find sufficient number of participants. The most successful recruitment was done for the experiments with the advanced stationary simulator in Sweden. The gender distribution rather reflects the situation among train drivers in Sweden (1 female out of 21 subjects) and also other countries (9% female and 81% male). It was also a problem to find inexperienced train drivers (less than 2 years of driving) compared to experience (more than 5 years driving). There were 26% novices and 74% experienced according to


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Table 14. The alert/fatigue condition was controlled by the experimenters and thus equally distributed. Despite the encountered problems, it was considered that the number of participants was sufficient for the analysis.

Table 14 Distribution of train drivers with respect to country, gender, experience, and driver

state

Country Number Gender Experience State

Female Male Experienced Novice Alert Fatigue

France 6 0 6 6 4 2 Great Britain 19 3 16 11 8 10 9 Israel 14 0 14 11 3 7 7 Italy 18 1 17 16 2 8 10 Sweden 21 1 20 16 5 10 11 Total portable

simulator 78 5 73 60 18 39 39

Advanced simulator SE 32 4 28 21 11 16 16 Grand total 110 9 101 81 29 55 55

9.2.1 Comments

It was not always an easy task to find the “right” participants, specifically recruiting train drivers and specifically female drivers. However, very valuable contacts were made during the recruitment which have been exploited in the further work and will be of great use in the future. Some problems were beyond control of the project. For example recruiting train drivers in Gothenburg (Sweden) started quite positive with good contacts with train operators but during the end of 2010 there were great changes among train operators and a Danish company took over the regional train services which meant great changes for many train drivers and the working situation was rather chaotic in Gothenburg. This likely contributed to problems in getting enough train drivers. However, 21 drivers is a good result compared to other countries (Table 14).

9.3 Installation and setup of the portable simulators

The simulators were shipped in specially made wooden boxes. Detailed descriptions on how to assemble the simulators were compiled (Annex 5) and distributes. Assembling was a quite simple task which took less than an hour. The remote control service (LogMeIn) was used to control and if needed adapt (e.g. change of language) the software. Instructions were also given on lighting, room space and sound levels. An ordinary office room was sufficient but there was also a need for the test leader to supervise the experiment from outside or inside the room without disturbing the participant.

9.4 Running the experiment

Overall, the actual running of the experiments went without any problems. Only a few subjects had to terminate the experiment due to sickness. There was a question about the sensation of sickness (1 0 not at all sick to 7 = very sick) and 90% scored “4” and below, less than 1% “7” and 68% “1”. This can be considered as a good result. Usually one or a few test leaders were responsible for the experiments. Alert participants were run before lunch and took less time compared to fatigued as they did not have to do the “boring drive” to induce fatigue. Usually it was only possible to run 2 drivers per day.


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9.5 Handling data

Uploading data to the FTP worked without problems most of the time. However, there were some minor problems related to connection errors and transfer speed. There were also some small mistakes with the subject coding but it was strictly recorded and corrected in WP5 before the actual analysis.

10. USE OF DATA – RULES OF ACCESS

All data recorded in WP4 will be available to project partners (employees and students) from a ftp site at VTI. An agreement has been signed by the partners which regulate the further exploitation of data collected in the ITERATE project. It was decided that data will be made available two years after the project has finished (i.e. December 2013). It is up to each partner to market and share data as they see fit.

• If data is shared with a third party the sharing partner has a responsibility to:

o Take reasonable effort to ensure that the data is not misused

o That the conclusions are sound given the nature of the data and how it was collected

o That ITERATE is properly acknowledged

o Provide the support necessary. VTI will not support third parts

o Inform other ITERATE partners if anything is published based on the data

• No partner should profit on the ITERATE project by charging third parties for the use of data.

When publishing new research based on the ITERATE project, make sure to communicate with the other ITERATE partners and allow a few weeks to comment or object.


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11. REFERENCES

Barnard, Y., Lai, F., et al. (2010a). Selection of operator support systems across modes (Project deliverable 2.2). ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium.

Barnard. Y.. F. Lai. et al. (2010b). Specification of test procedures for the simulator experiments (Project deliverable 3.1). ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium.

De Waard, D. (1996). The Measurement of drivers’ mental workload. Doctoral dissertation, Traffic Research Centre VSC, University of Groningen, The Netherlands.

Freyd, M. (1923) The graphic rating scale. Journal of Educational Psychology, 14, 83-102. Gillberg, M., Kecklund, G., and Åkerstedt, T. (1994). Relations between performance and subjective

ratings of sleepiness during a night awake. Sleep, 17(3), 236-241. Hayes, M.H.J., and Peterson, D.G. (1921) Experimental development of the graphic rating method.

Psychological Bulletin, 18, 98-99. Hoyle, R. H., Stephenson, M. T., Palmgreen, P., Lorch, E. P., & Donohew, R. L. (2002). Reliability

and validity of a brief measure of sensation seeking. Personality and Individual Differences, 32(3), 401-414.

Lai, F., Barnard, Y. et al. (2010). Review of existing technologies and systems supporting the operator (Project deliverable 2.1). ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium.

Oppenheim, I., Shinar, D. et al. (2010a). Critical review of models and parameters for diver models in different surface transport systems and in different safety critical situations (Project deliverable 1.1). ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium.

Oppenheim, I., D. Shinar, et al. (2010b). Description of Unified Model of Driver behaviour (UMD) and definition of key parameters for specific application to different surface transport domains of application. ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium (Project deliverable 1.2).

Reyner, L.A., Horne, J.A., (1997) Suppression of sleepiness in drivers: combination of caffeine with a short nap. Psychophysiology 34, 721–725.

Sagberg, F., & Bjornskau, T. (2006) Hazard perception and driving experience among novice drivers. Accident Analysis & Prevention, 38(2), 407-414.

Tapani. A.. Forsman. Å.. Vadeby, A., Yahya, M-R., Enjalbert, S., Cassani, M., Amantini, A., Lai, L., Kecklund, L., Arvidsson, M. (2011) Results from the analysis and input to development and validation of the statistical models. (Project deliverable 5.1). ITERATE (IT for Error Remediation And Trapping Emergencies) Consortium.

Wilkinson, R. T., & Houghton, D. (1982). Field test of arousal: A portable reaction timer with data storage. Human Factors, 24, 487-493.

Zijlstra, F.R.H. (1993) Efficiency in work behaviour: a design approach for modern tools. Ph.D. thesis, Delft University of Technology, Delft, The Netherlands.

Özkan, T., Lajunen, T., Wallén Warner, H., & Tzamalouka, G. (2006) Traffic climates and driver behaviour in four countries: Finland, Greece, Sweden and Turkey. Paper presented at the 26th International Congress of Applied Psychology, Athens, Greece, 16-21 July.


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12. ANNEX 1 EXPERIMENTAL PROTOCOLS

12.1 Experimental procedure for Car drivers

The following procedure was used for the car drivers.

1. Scheduling according to condition Alert/Fatigue – before or after lunch

2. Welcome and information about the experiment (written and oral)

3. KSS score

4. Signing informed consent

5. Reading instructions for the driving task, questions?

6. Cell phone off, toilet?, water?

7. IF fatigue BORING Drive Car (25 Minutes) after KSS (optional)

8. Training (10 minutes) system 1 (ISA/FWC) and counting task (1 and 7)

9. Questions?

10. Driving system 1 (ISA/FWC) 25 minutes

11. Intermission, toilet?

12. Training (10 minutes) system 2 (FWC/ISA)

13. Questions?

14. Driving system 2 (FWC/ISA) 25 minutes

15. KSS score

16. Hazard perception test (13 video clips) with one critical situation per clip (approx. 15

minutes)

17. Web questionnaire (approx. 20 minutes)

18. Other questions?

19. Financial compensation (different for each test site)

20. End and good bye

12.1.1 Information about the car and systems (ISA and FCW)

The following written information was given to all participants prior to the training and test ride. The instructions were translated in to all five languages used.

12.1.1.1 Background

The study, in which you have been invited to participate, seeks to investigate how drivers cope with various driving scenarios in the presence of given driver assistance systems. This study is part of a research project funded by the European Commission and will help us to more fully understand the interaction between the driver, the assistance systems, and the road environment.

12.1.1.2 The simulator experiment

This experiment involves driving on two stretches of roads. The scenario that we want to imagine yourself in is as though you are driving to a destination with a desired purpose (e.g. on your way home or to visit a friend). Rural road: this is a stretch of single carriageway road consisting of rural sections and a few villages. You will experience an in-vehicle speed management system, which will warn you when the vehicle speed is over the posted speed limit as well as when approaching a sharp bend, or a new speed limit which is lower than the current speed limit; for example, when approaching a village from a rural section.


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Motorway: this is a stretch of 2-lane motorway with moderate traffic flow. You will experience an in-vehicle collision warning system, which will warn you when a potential collision with the lead vehicle is likely to occur. Please drive the simulator as you would if it were a real vehicle in the real world (e.g. taking due care while driving and obeying traffic regulations etc). Motorway speed limit is 110 km/h

12.1.1.3 The additional task

While you are driving, an automated message will instruct you to carry out a counting-back task. For example, you may hear the following instruction: ‘Please count backwards in 7 from 949. Start when you are ready’ Your task is therefore announcing the following numbers in sequence: 949, 942, 935, 928, 921 etc. Please carry on doing so until you hear the instruction: ’Please stop the counting-back task’ Your performance on the counting-back task will be monitored by the researcher. Please try to maintain your driving performance (i.e. driving safely) and try to carry out the counting-back task as quickly and accurately as you could.

12.1.1.4 Experiment duration and payment

Each road will take approximate 25 minutes for completion. There is a break between the two drives. There are questionnaires for you to complete before and after the experiment. You will also be invited for a practice drive to allow you to become familiar with the simulator prior to the experiment taken place. The total duration of your participation will be approximately 2 hours. You will receive X Euro (slightly different at each site) at the end of the experiment as a token of appreciation for your time.

12.1.1.5 Ethics, safety and confidentiality

It is important that you understand that we are not looking at your individual driving style or judging your ability as a driver. We are solely interested in the behaviour of a group of drivers to draw conclusions about drivers in general. As with all our research, this study is subject to the strict ethical guidelines and the requirements of the Data Protection Act. In particular please note that:

• At no time now, nor in the future, will any information you provide be published that allows

you as an individual to be identified.

• You are free to withdraw from the study at any time without having to give any reason for

your decision.


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12.2 Experimental procedure for Train drivers

The following procedure was used for the train drivers.

1. Scheduling according to condition Alert/Fatigue – before or after lunch

2. Welcome and information about the experiment (written and oral)

3. KSS score

4. Signing informed consent

5. Reading instructions for the driving task, questions?

6. Cell phone off, toilet?, water?

7. IF fatigue BORING Drive Car (25 Minutes) after KSS (optional)

8. Training (30 minutes) same route as for real drive, speed keeping, stop at stations, counting

task

9. Intermission, questions, toilet?

10. Real drive (85 minutes), keeping time schedule, stop at stations, keeping speed, counting

(steps of 1 (medium workload) and steps of 7 (high workload))

11. KSS score

12. Hazard perception test (13 video clips) with one critical situation per clip (approx. 15

minutes)

13. Web questionnaire (approx. 20 minutes)

14. Other questions?

15. Financial compensation

16. End and good bye

12.2.1 Information about the train, controller and display

Figure 10 Simulated train (Bombardier Regina)

The train used in the simulation was modelled after a Bombardier Regina train (Swedish Designation X50), which is a multiple unit train with 3 cars (Figure 10). Total length is 54 meters. Top speed is 180km/h. They drove on a single track line derived from a real railway line in southern Sweden. The drive was about 100 km long and took approximately 1 hour and 25 minutes to drive.


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The train control for the portable simulator is shown in Figure 11. Speed was controlled by the right most lever (forward – accelerate) and the lever beside is used to control the brake (push forward to brake). This is not what most train drivers are used to but still they usually thought it was OK.

Figure 11 Train control for the portable train simulator

An original train control from a Bombardier Regina was used in the stationary train simulator, accelerate forward and brake backwards (Figure 12). Unlike the real train there was no cruise control function included. Thus, the driver had to actively control the speed.

Figure 12 Train control for the stationary train simulator (Bombardier Regina)

12.2.1.1 ETCS Display

The display functionality is depicted in the following. Figure 13 shows driving in “ERTMS fashion”. The icon right of the speedometer indicates that we are driving in full supervision mode. The current speed is indicated with both the arrow and numerical value in the centre of the arrow. The dark grey arc around the speedometer indicates the currently allowed speed.

Figure 13 ETCS display in normal drive mode


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The driver is driving on a track with speed limit 90 km/h. But he is currently running at 99km/h. Since his speed is above the allowed speed limit he will get a speed warning message from the ETCS display. Along with the displayed warning, he will also get an audible warning (Figure 14)

Figure 14 ETCS display speed warning

The driver is driving on a track with speed limit 90 km/h. But this time he is exceeding the speed limit with more than 9 km/h (in this case 18 km/h more than allowed). The driver will now get an over-speed warning message from the ETCS display along with an audible warning (Figure 15)

Figure 15 ETCS display over speed warning

In this picture the driver is driving at 40 km/h. He has received a notification that ahead is a stop. The bar on the left indicates the distance to the stop. The number above the bar indicates the exact distance (in this case 772 meters). The dark green arc around the speedometer has been replaced with a light grey arc. This means that the current speed is allowed but as we approach the stop this arc will shrink. Also note the small square in the upper left hand corner. This square will grow as we approach the point where braking has to start to be able to safely reach standstill. (Figure 16)


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Figure 16 ETCS display new speed ahead

In this picture the driver is driving at 140 km/h. But he has got a notification about a new lower speed ahead, in this case 90 km/h. The bar on the left says that he has 845 meters left to the new speed. Also note the small square in the upper left hand corner. This square will grow as we approach the point where braking has to start to be able to safely reach the new speed. (Figure 17)

Figure 17 ETCS display new lower speed

In this picture the driver has begun to brake but his breaking has probably begun to late. His brake curve does not match the brake curve for this train and the ETCS display is displaying a speed warning message. Also note that the small square has grown to maximum size and has also changed colour. (Figure 18)

Figure 18 ETCS display new speed and too late braking

In this image we see that the driver has not been able to brake enough and his speed will not be able to match the new future speed and he will get a over speed warning message. Also note that the square is still in maximum size and has also changed colour. (Figure 19)


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Figure 19 ETCS display new speed and too late braking warning

12.2.1.2 Instructions for the drive

The driver was told to drive as he/she would do in a similar real train. In the ETCS display there was a digital clock at bottom right. Training started at 11:00 and the experimental drive started at 12:00. The timetable for the experimental drive is shown below (Table 15). There was a printed version of the time table beside you while you drive. The driver was told to make a 30 second stop at all stations except Bjorn and follow the time table.

Table 15 Time table for the experimental drive

Station Depart Stop

Alhpa 12:00:00 Start Bjorn 12:06:00 - Charlie 12:14:00 00:30 Davidtown 12:23:00 00:30 Ertico 12:32:00 00:30 Franktown 12:39:00 00:30 Golden 12:49:00 00:30 Habo 12:56:00 00:30 Ilito 13:05:00 00:30 Jamboree 13:14:00 00:30 Kitewill 13:20:00 00:30 Lulu Stop Instruction to the participant: Before you perform the actual test drive you will make a training drive (approx. 30 minutes)

to experience and get used to the simulator and the train control.

12.2.1.3 Counting task

While you are driving, an automated message will instruct you to carry out a counting-back task. For example, you may hear the following instruction: ‘Please count backwards in 7 from 949. Start when you are ready’

Your task is therefore announcing the following numbers in sequence: 949, 942, 935, 928, 921 etc. Please carry on doing so until you hear the instruction:


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’Please stop the counting-back task’

Your performance on the counting-back task will be monitored by the researcher. Please try to maintain your driving performance (i.e. driving safely) and try to carry out the counting-back task as quickly and accurately as you could.

12.2.1.4 Ethics

It is important that you understand that we are not looking at your individual driving style or judging your ability as a driver. We are solely interested in the behaviour of a group of drivers to draw conclusions about drivers in general. As with all our research, this study is subject to the strict ethical guidelines and the requirements of the Data Protection Act. In particular please note that:

� At no time now, nor in the future, will any information you provide be published that allows you as an individual to be identified.

� You are free to withdraw from the study at any time without having to give any reason for your decision.

12.2.1.5 Ready?

• Any questions?


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13. ANNEX 2 WEB QUESTIONNAIRES

The following questionnaires were used in the experiments. Car drivers had to answer 99 questions in total, divided in to 6 sections. Train drivers answered 80 questions divided in 5 sections. Some of the questions were common for both car and train drivers. All questionnaires were translated in to Swedish, Italian, French and Hebrew. SPSS Dimensions Net ® was used to set up the questionnaires and the database is located at VTI in Sweden. Collected data can easily be exported to data files for statistical analysis. The variable names as they appear in the SPSS data file can be found in parenthesis after the questions (green text). There are some initial variables as follows: Variable Values

Country

1=GB 2=FR 3=Israel 4=Italy 5=SE

Sim_type

1=Car_Mobile 2=Train_Mobile 3=Car_Advanced 4=Train_Advanced

Respondent_ID e.g. SE01CA, GB03TA according to the naming principle of subjects.

DataCollection_StartTime CET time when interview started DataCollection_FinishTime CET time when interview ended

1 Common introductory questions concerning driving Introduction

To start with we would like to know how you think the simulator drive went. Please indicate your preferred alternative for each item

Question Sub question Answer 1. How do you think the driving went? (Drivingwent)

1 = very badly to 7 = very well

2. How realistic do you think the simulator driving was? (Realistic)

1 – not at all realistic to 7 - very realistic

3.Did you get bored during the drive? (Bored)

1 – not at all bored to 7 - very bored

4. Did you get tired during the drive? (Tired)

1 – not at all tired to 7 - very tired

5. Did you ever feel sick during the drive? (Sick)

1 – not at all sick to 7 - very sick

2 Background (car) Introduction

We would also like to ask you some background questions. Please try to answer all questions!

Question Sub question Answer

6. Sleep diary Sleep (Sleepeat_Sleep_GV101 – 125)

Indication by hours – when?


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Nap (less than 2 hours sleep) (Sleepeat_Nap_sleep_less_t_GV101 - 125) Food (Sleepeat_Food_GV101- 125) Coffee/tea/coca cola/ pepsi/energy drink (Sleepeat_Coffee_tea_coca_GV101 - 125)

7. When were you born? Select the right year from the list below. (Born)

Year

8. Gender? (Gender) Female, Male

9. What type of driving license do you have and which year did you acquire it? Answer by filling in the year (e.g. 1994) in the field. Indicate the categories that you don't have with 0.

A Motorcycle (Quest241_Motorcycle_year1)

B Passenger car (Quest241_Passenger_car_year1)

C Truck (Quest241_Truck_year1)

D Bus (Quest241_Buss_year1)

BE Passenger car with heavy trailer (Quest241_Passenger_car_wi_year1)

CE Heavy truck (Quest241_Heavy_truck_year1)

DE Bus with trailer (Quest241_Buss_with_traile_year1)

10. How many accidents (count even the smallest crashes) have you been involved in as a driver during the last 3 years (Crashes)

Integer

11. How much did you drive last year? Please, answer in km. (Mileage)

Kilometres

12. How often do you drive with a system that informs you of the current speed limit and/or warns you if you exceed this limit (e.g. as part of a navigation system)? (ADAS_Speedwarning_GV1)

never

sometime

always

13. How often do you drive with a forward collision warning system activated? (ADAS_collwarning_GV1)

never

sometime

always

14. Do you have any previous experience from driving in a driving simulator? (Simexp)

Yes No


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3 Life style (Brief SSS (Sensation Seeking Scale)) common for both car and train drivers

Introduction We would now like to ask you some questions about your general attitudes to life. How strongly do you agree or disagree with each of the following? Please indicate how strongly you agree or disagree with each item. We are interested only in your likes or feelings, not in how others feel about these things or how one is supposed to feel. There are no right or wrong answers. Be frank and give your honest appraisal of yourself.

Question Sub question Answer 1. I would like to explore strange places

(Life_style15)

strongly disagree

disagree

neither disagree nor agree

agree

strongly agree

2. I get restless when I spend too much time at home (Life_style16)

3. I like to do frightening things (Life_style17)

4. I like wild parties (Life_style18) 5. I would like to take off on a trip with

no pre-planned routes or timetables (Life_style19)

6. I prefer friends who are excitingly unpredictable (Life_style20)

7. I would like to try bungee jumping (Life_style21)

8. I would love to have new and exciting experiences, even if they are illegal (Life_style22)

4 DBQ (Driving Behaviour Questionnaire) Car Introduction

How often do you do each of the following? Please indicate how often, if at all, this kind of thing has happened to you. Base your judgments on what you remember of your driving over the past year.

Question Sub question Answer 1. Sound your horn to indicate your

annoyance to another road user (DBQ23)

never

hardly ever

occasionally

quite often

frequently

nearly all the time

No Answer

2. Pull out of a junction so far that the driver with right of way has to stop and let you out (DBQ24)

3. Disregard the speed limit on a residential road (DBQ25)

4. Drive when you suspect you might be over the legal blood alcohol limit (DBQ26)

5. Become angered by another driver and give chase with the intention of giving him/her a piece of your mind (DBQ27)

6. Stay in a motorway lane that you know will be closed ahead until the last minute before forcing your way into the other lane (DBQ28)

7. Overtake a slow driver on the inside (DBQ29)

8. Race away from traffic lights with


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the intention of beating the driver next to you (DBQ30)

9. Drive so close to the car in front that it would be difficult to stop in an emergency (DBQ31)

10. Cross a junction knowing that the traffic lights have already turned against you (DBQ32)

11. Become angered by a certain type of driver and indicate your hostility by whatever means you can (DBQ33)

12. Disregard the speed limit on a motorway (DBQ34)

5 DAQ (Driving Attitude Questionnaire) Car only Introduction

How often do you do each of the following? Please indicate how often, if at all, this kind of thing has happened to you. Base your judgments on what you remember of your driving over the past year.

Question Sub question Answer 1. People stopped by the police for

close-following are unlucky because lots of people do it (DAQ35)

strongly disagree

disagree

neither disagree nor agree

agree

strongly agree

2. Speed limits are often set too low, with the result that many drivers ignore them (DAQ36)

3. Close following isn’t really a serious problem at the moment (DAQ37)

4. I know exactly how fast I can drive and still drive safely (DAQ38)

5. I would favour stricter enforcement of the speed limit on residential roads (DAQ39)

6. Some people can drive safely even though they only leave a small gap behind the vehicle in front (DAQ40)

7. Even driving slightly faster than the speed limit makes you less safe as a driver (DAQ41)

8. I would be happier if close-following regulations were more strictly applied (DAQ42)

9. Stricter enforcement of speed limits on residential roads would be effective in reducing the occurrence of road accidents (DAQ43)

10. Even driving slightly too close to the car in front makes you less safe as a driver (DAQ44)

11. On the whole people aren’t aware of the dangers involved in close following (DAQ45)

12. I would be happier if the speed limits were more strictly enforced (DAQ46)

13. Harsher penalties should be introduced for drivers who drive too close to the car in front (DAQ47)

14. It’s OK to drive faster than the speed limit as long as you drive carefully


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(DAQ48) 15. People stopped by the police for

speeding are unlucky because lots of people do it (DAQ49)

16. I think the stopping distances in the Highway Code are too great for people to take notice of them (DAQ50)

17. Speeding is one of the main causes of road accidents (DAQ51)

18. It is quite acceptable to drive close to the car in front than is recommended (DAQ52)

19. Sometimes you have to drive in excess of the speed limit in order to keep up with the flow of traffic (DAQ53)

20. I would favour a clamp down on drivers who drive too close to the vehicle in front (DAQ54)

6 Culture – common questions to both car and train drivers

Introduction Finally, we would like to ask you some questions about the traffic situation in your country. First set of questions. Below, some words are given to describe the traffic system, environment and atmosphere in our country. Please indicate how well these words describe the traffic situation in our country.

Question Sub question Answer 1. Dangerous (Culture1) 2. Dynamic (Culture2) 3. Disorganised (Culture3) 4. Aggressive (Culture4) 5. Exciting (Culture5) 6. Fast (Culture6) 7. Stressful (Culture7) 8. Monotonous (Culture8) 9. Depends on ones luck (Culture9) 10. Demands alertness (Culture10) 11. Depends on ones fate (Culture11) 12. Demands cautiousness (Culture12) 13. Requires experience (Culture13) 14. Requires being quick (Culture14) 15. Demands compliance (Culture15) 16. Non-compliance is rewarding

(Culture16) 17. Makes one feel worthless (Culture17) 18. Mobile (Culture18) 19. Creates tension (Culture19) 20. Includes precautionary measures

(Culture20) 21. Under enforcement (Culture21) 22. Commute easily from one place to

another (Cultur22) 23. Requires mutual courtesy (Cultur23) 24. Planned (Culture24) 25. Pressurizing (Culture25) 26. Forgives mistakes (Culture26) 27. Includes deterring rules (Culture27)

Does not describe it at all

Does not describe it

Describes it a little

Somewhat describes it

Describes it

Very much describes it

No Answer


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28. Risky (Culture28) 29. Chaotic (Culture29) 30. Requires patience (Culture30) 31. Makes one irritated (Culture31) 32. Requires vigilance (Culture32) 33. Requires skilfulness (Culture33) 34. Harmonious (Culture34) 35. Time consuming (Culture35) 36. Annoying (Culture36) 37. Egalitarian (Culture37) 38. Safe (Culture38) 39. Functional (Culture39) 40. Free flowing (Culture40) 41. Requires knowledge of traffic rules

(Culture41) 42. Directs one's behaviour (Culture42) 43. Unpredictable (Culture43) 44. Intense (Culture44) Comments (comments)

Train specific questions 2 Background data (train)

Introduction We would also like to ask you some background questions. Please try to answer all questions!

Question Sub question Answer 9. When did you first start working as a licensed train driver? (Year) (Yearstart)

Year

11. What type of train do you usually operate? (Several alternatives possible) (Lictype)

1. Commuter train (suburban)

(Trainoperate1)

2. Commuter train (regional)

(Trainoperate2)

3. Long distance train / Inter-city

train (Trainoperate3)

4. High-speed train

(Trainoperate4)

5. Freight train / Goods train

(Trainoperate5)

12. How often have you've been involved in the following incidents during the last 3 years

Signals Passed At Danger (SPAD) (Incident_Signals_Passed)

Never, sometimes , often

Application of emergency brakes (Incident_Application)


Tearing down the overhead lines (Incident_Tearing_down)


13. How many of the following accidents have you been involved in as a train driver during the last 3 years?

Have you ever been involved in an accident involving (wild) animals? (Accident_a_Animal)

Yes/no , Integer (Numberanimals)

Have you ever been involved in an accident involving humans? (Accident_b_Humans)

Yes/no, Integer (Numberhumans)

Have you ever been involved in an Yes/no, Integer


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accident involving other objects? (e.g. cars, bicycles, bulky debris placed on track) (Accident_c_Objects)

(Numberobjects)

14. How often do you operate the train on lines without automatic safety systems (e.g. ATC, ATP, AWS) due to technical malfunction, or because of track maintenance work? (Automatic_system_without)


15. How often do you experience errors from the automatic safety system? (Automatic_system_errors)


16. Do you have previous experience of the ETCS/ERTMS safety system? (ETCS_ERTMS_exp)

Yes, No

4 DBQ (Driving Behaviour Questionnaire) Train – New questionnaire Introduction

The next set of questions covers how often you do various things while driving a train. How often do you do each of the following? Please indicate how often, if at all, this kind of thing has happened to you Base your judgments on what you remember of your driving over the last three years.

Question Sub question Answer 1. Drive the train unaware that the

automatic safety system has been temporary disabled (DBQ26_T)

never

hardly ever

occasionally

quite often

frequently

nearly all the time

No Answer

2. Insufficient braking when approaching a platform consequently missing the platform/train stop. (DBQ27_T)

3. Unintentionally typed in incorrect values in the automatic safety system (DBQ28_T)

4. Neglect (unintentionally or deliberately) to focus attention on potential risk factors (e.g. people, cars, etc.) when approaching a railway crossing (DBQ29_T)

5. Drive the train “too fast” with the intention to reduce a delay in the timetable (DBQ30_T)

6. Passing a red signal (SPAD) unintentionally (DBQ31_T)

7. Deliberately passed a red signal (SPAD) without approval from traffic control officer (DBQ32_T)

8. Drive the train over the speed restriction even though there is no delay in the timetable (DBQ33_T)

9. Reversed the train without approval from traffic control officer (DBQ34_T)

10. Unknowingly exceeding the speed


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limit due to insufficient presentation of current speed (DBQ35_T)

11. Driving or accelerating too fast, thus resulting in automatic service brakes being applied (DBQ36_T)

12. Application of automatic service brakes, due to signal passed at danger (intentionally or unintentionally) (DBQ37_T)


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14. ANNEX 3 HAZARD PERCEPTION TEST

How to perform the test

Position the subject on a chair in front of the computer screen with a distance between the screen and the subjects of about 60 cm. Minimum required size for the screen is 17’.

1. Start test by opening ”reaksjonstest02.exe”

2. Click on ”Instruktion” and instead for using the sound, switch off the sound and read

following (Note!: you might need to train few times yourself in order to be coordinated

with the video when you read the text).

The following instruction should be read by the test leader to the participant.

In traffic, there are sometimes unforeseen situations that allow you as a driver must be prepared to react quickly, for example by braking suddenly or swerve. The video recordings that you soon will see present such situations. Video recordings are made from a car where the camera is placed near the driver's seat so that the traffic picture is similar to what the driver sees. Imagine that you are driving the car as the videos are filmed from. It is important to pay attention to traffic situations which may mean that you must be prepared to brake hard or steer to avoid an obstacle. When you detect such dangerous situation, you should as soon as possible press the space bar. You should not wait to press to see if the situation gets really dangerous, but pressing immediately when you see that this could* develop into a dangerous situation. It can be for example a pedestrian who suddenly goes out into the street without looking for, children playing on the sidewalk, a ball that rolls into the street, stop light or flashing running lights at the forefront, other road users who do not follow rights of way or other different situations which requires you to be prepared to react quickly. Before the test, you will see an example. (*comment: after reading that, repeat one more time to the subject that they should not wait to see whether a situation is dangerous or not but rather press the space bar a.s.a.p. when they interpret the situation as dangerous)

3. Ask the subject whether they want you to read one more time if they have missed some

part.

4. Click on ”training” (same here, switch off the sound and read the instructions instead):

In a few moments and you'll see a car coming from the left which must give way to you. Soon the car starts to drive, which means you must be prepared to slow down. However, you can see that the car is accelerating so quickly that that there is no risk of collision, but you could not know that when the car started to drive. If you see a similar situation in the test, you will have press the space bar as soon as you see when a car or other road unexpectedly begin to move so that you may have to slow down or steer to avoid danger. As an exercise, the situation is showed once more and you can press the space bar when you see that car on the left begins to drive. Now you will see that the car starts to run. Now you can choose to start the test or see the example again.

5. Click on ”Ta testet”. The first screen just remind you that when something happen you’ll

have to press the space bar. Then, fill in yourself the information required:

English text Norwegian text


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About you Name Age Gender: Women/Man For how long you have your driving licence (years and months; no driving licence) Click “ready”

OM dig Fornamn Alder Kjon: Kvinne/Mann Hvor lenge har du hatt forerkort for bil? (år, måneder, har ikke forekort) ’Ferdig’

6. After you click on the Ready button the program will be starting automatically. Make

your subject push the button so that they are in position to start directly.

It is in total 13 video sequences. To close the test you’ll have to click “Contrl+ Alt+ Delete” and close the activity (there is no other way to do it). Control the two files that are created where all answers are collected: Teststed1.csv: contains one reaction time for each video of the predefine event to react for. Teststed1alle.csv: contains all the reaction time for all events where the subject push the space bar. Interpretation of data from the test There are two output data files: 1. Teststed1.csv 2. Teststed1alle.csv. The first (Teststed1.csv) shows the first reaction time within the defined time window in consecutive columns as follows:

A. Time B. Date C. Name D. Age E-F. Time with driving license (E: years, F: months) G. No driving license (code 1) H. Gender (Kvinne/Mann) I. 1 (Situation 1) J. Reaction time for situation 1 (in seconds) K. 2 (Situation 2) L. Reaction time for situation 2 M. 3 (Situation 3) N. Reaction time for situation 3 O. 1 (Situation 4) P. Reaction time for situation 4 Etc. up to situation 13 In case there was a miss it is indicated with 999

Reaction time is defined as the time from start of the event as defined by the time window per situation.

Video

numb

er

Description of ’risk’

Definition of start

of hazard

perception

window

End of

hazard

perception

window

Windo

w

Length

1 White car coming from left 8 15 7


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2 Green car breaks and turn left 7 13 6 3 Children + adult crosses the street 11 23 12 4 Cyclists coming towards me on the right side 38 48 10 5 Two cyclists in each direction in dusk, were

one of them I discover late on the left side 13 38 25

6 Car suddenly breaks and make turn to make a parallel parking

9 24 15

7 Hard to identify hazard, cyclists biking towards me on the right side? 0 10 10

8 Roller skater after buss 2 9 7 9 Car coming from petrol station on the left 1 7 6 10 Ambulance coming from right 4 9 5 11 Red bus suddenly comes from left 31 41 10 12 Unsure of hazard, tram that decrease my

visibility or the bicycle suddenly coming from right?

14 22 8

13 Hazard hard to identify, people standing under bridge? 3 8 5

At the end of the test the subject will get the following feedback

Number of correct

reaction times (i.e. in

the time window)

Feedback on the screen English

9 – 13 Du oppfater faresituasjonene svært godt

You perceive/identify the risks very good

5 – 8 Du oppfatter faresituasjonene ganske godt

You perceive/identify the risks rather good

< 5 Du trenger mer trening på å oppfatte farene i trafikken

You need more training in order to identify the traffic risks

The file Teststed1alle.csv contains all reaction time (presses on the space bar) even those outside the time windows. However the starting point is start of the video sequence in this case. This file can be used as an indicator of the data quality e.g. if the subjects keep on pressing the space bar in order to hit by chance it will be shown in this file. Thus, we can consider this file as optional for the analysis.


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15. ANNEX 4 INFORMED CONSENT FORM

This is a draft form that each partner translated and adapted to their specific situation. Study description

(Instruction to the test leader: provide a verbal description but make them also read)

The project ITERATE (IT for Error Remediation And Trapping Emergencies) is a collaborative project within the 7th Framework Program. The objective of ITERATE is to develop and validate a unified model of driver behaviour (UMD) and driver interaction with innovative technologies in emergency situations. The aim of this simulator trial is to study driving behaviour for different groups of drivers under various conditions.

During the simulator drive we will record various driving behaviour data. You will also answer a number of questions. You participate on a completely voluntary basis. You can at any time terminate your participation without having to provide an excuse. If you abort your participation we will destroy and not use data recorded during you participation.

You will drive in a simulator. However, we would like to stress that you should behave according to rules and regulations that apply in real life.

Recorded data will be separated from your identity. We are only interested in analysing data on group level. We certify to treat collected data according to good practice and follow sound ethical rules. Unidentified data will be analysed by VTI and other research institutes.

If you have any questions or comments concerning this study you can ask the test leader or contact the person responsible for the study:

Name

Address

Phone

Email

Participant’s consent

The test leader has described the purpose of the study and I know the preconditions that apply. Possible questions I had have been answered satisfactory. I am aware that driving behaviour and questionnaire data will be collected and analysed. I know that I can at any time decide to quite the test without any reason.

I ___________________________ participate voluntarily in this study. Name

Signature: ___________________________ Date: ____________

Agreement to use pictures and video recordings (Optional), participant were asked if they agreed that photos and video recording could be used for dissemination of results.


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16. ANNEX 5 SETTING UP THE SMALL SCALE PORTABLE

SIMULATOR

Build the simulator from the box

Short version

This procedure will take about 40 minutes. Take out all the boxes from the upper shelf. Remove the piece of wood holding the monitor stand. Unload the big screen on the monitor stand, two persons to do it. The open box can be seen below with sound system, train controller and computer still inside.

Screen/Monitor stand

The large screen on the stand is called primary screen. The screen can be tilted and moved up and down. If it is not staying in position, open the top cover of the monitor stand (see picture below) and screw to ‘+’. The centre of the screen should be at eye level of the subject and distance to screen should be as close as possible (see further down).

Chair

Some instructions are present into the box to assemble the chair. We also added white pieces of tape here and there that helps you to assemble the chair. See following pictures for help.


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The stand for the secondary screen and the gear is in three pieces, you see below how it look like when assemble, you have two pieces to add showed with the arrows.

Check that both the primary and the secondary (small) screen are in horizontal position. The secondary screen should be the lowest possible level for all subjects. Place the steering wheel on the “table” in front of the small screen and the gearshift on the small “table” beside (right). Computer

Place the computer between the screen and the stand for the control (see above). Place the subwoofer under the chair and both speakers (frontal) on each side of the computer. The train and car controls have USB connections to the computer. NOTE! You cannot have booth train control and car controls connected at the same time to the computer – it will cause a conflict and the software will not work. Turn on the computer and screen

Switch on the screen by pressing the button on the back, turn on the computer and push the button to turn on all three speakers. Login: ITERATE Password: qwerty-2010 Remarks! The computer should NOT be connected to internet while running an experiment!


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Please make sure the screen saver is OFF! Screen configurations

You probably need to configure the simulator only once when you install the simulator for the first time. But check if you have short or very long subjects that seat and screen are in the right position. However, make always sure that the big screen is adjusted to the eye sight height of the subject. Location of screen, instruments and chair

The following distances should be used. Eye sight level: At the level of the focus of expansion. To be adjusted for each subject for the primary screen. Distance primary to secondary screen: 60 cm between both screens pillar. The room needs to be dark (preferably without any windows) and with air condition since the machine produce a lot of heat. Two IKEA lamps were used to provide standardised light conditions. More details were provided to each test site.

Permission granted to use the pictures above in Annex 5 by those appearing on the photos.

data and experimental protocol from the experiments (d4.1) · deliverable no. 4.1 dissemination...

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