distraction and drowsiness – a field...

VTI rapport 638APublished 2009

www.vti.se/publications

Distraction and drowsiness – a field studyTechnical report

Katja Kircher

Albert Kircher

Fredrich Claezon

Publisher:

Publication:

638A

Published:

2009

Project code:

40658

Dnr:

2006/0226-26

SE-581 95 Linköping Sweden Project: IVSS Distraction and Drowsiness

Author: Sponsor: Katja Kircher, Albert Kircher and Fredrich Claezon Saab, within IVSS programme

Title: Distraction and drowsiness – a field study. Technical report

Abstract (background, aim, method, result) max 200 words:

The main goal of the distraction and drowsiness field study was to evaluate a system for detecting driver distraction and drowsiness. This report focuses on the system implementation and the algorithms detec-ting distraction and drowsiness.

A vehicle was instrumented with video cameras, an automatic eye tracker and GPS receivers. Further data were read from the CAN bus of the car. The data were logged continuously with high frequency. The log system operated autonomously. Seven participants drove the vehicle during one month each. During the first ten days a behavioural baseline was collected. Afterwards the warnings were activated, such that the drivers received distraction warnings in form of a vibration in the seat when the algorithm determined that they had looked away from the forward roadway too much. A separate algorithm judged whether the drivers were drowsy or not. Questionnaires were administered on three occasions during the course of the study.

No major problems were encountered during the field operational test (FOT), but a number of smaller problems had to be solved. However, in the end of the data collection period the computer installed in the car became more and more unstable, which led to increased data loss.

Keywords: distraction, field study, eye tracking, methodISSN: Language: No. of pages:

0347-6030 English 66 + 7 Appendices

Utgivare: Publikation:

638A

Utgivningsår:

2009

Projektnummer:

40658

Dnr:

2006/0226-26

581 95 Linköping Projektnamn: IVSS Distraction and Drowsiness

Författare: Uppdragsgivare: Katja Kircher, Albert Kircher och Fredrich Claezon Saab, inom IVSS-programmet

Titel: Distraktion och sömnighet – en fältstudie. Teknisk rapport

Referat (bakgrund, syfte, metod, resultat) max 200 ord:

Huvudmålet med distraktions- och sömnighetsstudien var att utvärdera ett system för att detektera förar-distraktion och sömnighet. Denna rapport fokuserar på systemimplementationen och algoritmerna som detekterar distraktion och sömnighet.

En försöksbil utrustades med videokameror, en automatisk eye tracker och GPS-mottagare. Dessutom loggades data från fordonets eget nätverk (CAN). Datamaterialet lagrades kontinuerligt med hög frekvens. Loggsystemet fungerade autonomt. Sju deltagare körde fordonet under en månad var. Under de första tio dagarna samlades data om vanligt körbeteende utan varningssystem (baseline). Sedan aktivera-des varningarna, vilket innebar att förarna fick en varning i form av en vibration i förarsätet när algorit-men bedömde att de hade tittat bort från vägen för länge. En separat algoritm bedömde om förarna var sömniga. Enkäter fylldes i vid tre tillfällen under studiens gång.

Inga större problem uppstod under försökstiden, men ett antal mindre problem behövde lösas. I slutet på försöksperioden blev logg-datorn mer och mer instabil, vilket ledde till ökat databortfall.

Nyckelord:

distraktion, fältstudie, eye tracking, metod ISSN: Språk: Antal sidor:

0347-6030 Engelska 66 + 7 bilagor

VTI rapport 638A Cover: Tedd Soost

Preface This report is the second in a series of three. The first one is the literature review on driver distraction by Kircher (2007), which builds the theoretical foundation for the study described here. In this present report the method and procedure are described in detail, and the method is evaluated for its usefulness in the context of distraction mitiga-tion research. The third part of the series contains results of the study, together with a discussion of the results (Kircher, Kircher & Ahlström, 2009).

The authors would like to thank Henrik Otto (SmartEye AB) for contributing with a description of the real time eye tracker used in the present study (Chapter 4.3), and Serge Boverie (Continental Corporation) for providing the description of the drowsiness detection algorithm (Chapter 5.4).

We thank Arne Nåbo at Saab for trusting us with the conduction of this study, which let us explore new grounds. At VTI we thank Birgitta Thorslund (now ÅF) for helping us with recruiting and informing participants, Lena Nilsson for general support, and Karl Hill, Peter Ståhl and Carl-Johan Ydrevik for fantastic technical support.

Linköping March 2009

Katja Kircher

VTI rapport 638A

Quality review Review seminar was carried out on 18 December 2008 where Jan Andersson, VTI, reviewed and commented on the report. Katja Kircher has made alterations to the final manuscript of the report. The former research director of the project manager, Lena Nilsson, examined and approved the report for publication on 6 March 2009.

Kvalitetsgranskning Granskningsseminarium genomfört 2008-12-18 där Jan Andersson, VTI, var lektör. Katja Kircher har genomfört justeringar av slutligt rapportmanus 2008-12-29. Projektledarens tidigare chef Lena Nilsson har därefter granskat och godkänt publikationen för publicering 2009-03-06.

VTI rapport 638A

Table of Contents Summary............................................................................................................ 5

Sammanfattning ................................................................................................. 7

1 Introduction .............................................................................................. 9

2 Participants ............................................................................................ 10

3 Vehicle ................................................................................................... 11

4 Data acquisition system......................................................................... 12 4.1 Power module........................................................................................ 12 4.2 Data acquisition hardware ..................................................................... 13 4.3 Smart Eye Pro ....................................................................................... 15 4.4 Mobile hard disk..................................................................................... 17 4.5 GPS in the instrumented vehicle............................................................ 18 4.6 Digital mobile video recorder ................................................................. 21 4.7 VGA-FBAS video converter ................................................................... 24 4.8 Camera for driver monitoring ................................................................. 24 4.9 Monitor, keyboard, mouse ..................................................................... 26 4.10 Network.................................................................................................. 26 4.11 Audio mute box...................................................................................... 26 4.12 Software................................................................................................. 26

5 Inattention and drowsiness detection system ........................................ 30 5.1 World model car..................................................................................... 30 5.2 Inattention detection algorithm............................................................... 31 5.3 Distraction warning ................................................................................ 34 5.4 Drowsiness warning algorithm ............................................................... 34 5.5 Drowsiness aarning ............................................................................... 36 5.6 Inhibitions............................................................................................... 38 5.7 Manual ................................................................................................... 39 5.8 Display ................................................................................................... 39

6 Experimental design and procedure ...................................................... 44 6.1 Initial contact.......................................................................................... 46 6.2 Middle contact........................................................................................ 47 6.3 Final contact .......................................................................................... 47 6.4 Participant initiated contacts .................................................................. 48

7 Log data................................................................................................. 49

8 Discussion of method ............................................................................ 50

9 Lessons learned .................................................................................... 52 9.1 Participants ............................................................................................ 52 9.2 Vehicle ................................................................................................... 53 9.3 Design and procedure ........................................................................... 62 9.4 Data analysis ......................................................................................... 63

References ....................................................................................................... 65 Appendices

VTI rapport 638A

VTI rapport 638A 5

Distraction and drowsiness – a field study. Technical report

by Katja Kircher, Albert Kircher and Fredrich Claezon∗ VTI (Swedish National Road and Transport Research Institute) SE-581 95 Linköping Sweden

Summary The main goal of the distraction and drowsiness field study was to evaluate a system for detecting driver distraction and drowsiness. This report focuses on the system implementation and the algorithms detecting distraction and drowsiness. A previous report dealt with the background of driver distraction, the results of the study are presented in a further report.

A vehicle was instrumented with video cameras, an automatic eye tracker and GPS receivers. Further data were read from the CAN bus of the car. The data were logged continuously with high frequency as long as the ignition was on. The log system operated autonomously and was switched on with the turning of the ignition key. Seven participants drove the vehicle during one month each. During the first ten days the distraction and drowsiness warning system was deactivated, in order to collect a behavioural baseline. After this the warnings were activated, such that the driver received distraction warnings in form of a vibration in the seat when the algorithm determined that they had looked away from the forward roadway too much. A separate algorithm judged whether the drivers were drowsy or not. Three drowsiness levels existed, which led to three different warnings with increasing intensity for increasing drowsiness. The eye tracking system installed in the car afforded real time eye tracking, which is necessary for giving glance direction based or blink duration based warnings in real time.

The participants filled in questionnaires about their driving habits, their attitudes about driver distraction and drowsiness, and their expectations towards the warning system as well as their experiences with the system. A number of questionnaires were administered on three occasions during the course of the study.

No major problems were encountered during the field study, but a number of smaller problems had to be solved. However, in the end of the data collection period the computer installed in the car became more and more unstable, which led to increased data loss. Again, piloting was shown to be essential, as well as a clear delimitation of the goals and hypotheses of the project.

The obvious potential of the distraction detection system was pointed out by the positive comments of the participants, but having a system which is reliable in all situations and for all drivers is still a difficult task.

∗ Saab Automobile

6 VTI rapport 638A

VTI rapport 638A 7

Distraktion och sömnighet – en fältstudie. Teknisk rapport

av Katja Kircher, Albert Kircher och Fredrich Claezon∗ VTI 581 95 Linköping

Sammanfattning Det viktigaste målet med fältstudien om förardistraktion och -sömnighet var att utforska ett system som skulle detektera förardistraktion och sömnighet. Denna rapport fokuserar på systemimplementationen och algoritmerna som ska detektera distraktion och sömnig-het. En föregående rapport belyste bakgrunden för förardistraktion och resultaten finns i ytterligare en rapport.

En personbil instrumenterades med videokameror, en automatisk eye tracker och GPS-mottagare. Ytterligare data loggades från fordonets eget nätverk (CAN). Dataströmmen loggades kontinuerligt och med hög frekvens så länge tändningen var på. Logsystemet arbetade autonomt och startade när tändningen slogs på. Sju personer körde bilen under en månad var. Under de första tio dagarna var varningssystemet inaktiverat, för att logga referensdata (baseline). Efter detta slogs varningssystemet på, varpå förarna fick distraktionsvarningar som vibrationer i förarsätet när de hade tittat bort från vägen för mycket enligt algoritmen. En separat algoritm bedömde om förarna var trötta eller inte. Tre olika sömnighetsnivåer existerade, vilka ledde till tre olika varningar med ökande intensitet för ökande sömnighet. Eye tracking-systemet, som var installerat i bilen, erbjöd ögontracking i realtid, vilket är nödvändigt för varningar som ges baserade på blickriktning och blinkduration.

Deltagarna besvarade enkäter som handlade om deras vanliga körbeteende, deras in-ställningar angående förardistraktion och sömnighet, deras förväntningar om varnings-systemen och deras erfarenheter med varningssystemen. Enkäterna fylldes i vid tre olika tillfällen under försöksperioden.

Inga större problem dök upp under studiens gång, men ett antal mindre problem be-hövde lösas. Vid de sista körningarna blev datorn mer och mer instabil, vilket ledde till en ökad dataförlust. Även i denna studie visade det sig att förstudier (pilots) var mycket betydelsefulla, liksom en klar beskrivning av hypoteserna och målen i projektet.

Potentialen av ett distraktionsvarningssystem påpekades av de positiva kommentarerna som deltagarna gav, men det är än så länge svårt att leverera ett system som är pålitligt i alla situationer och för alla förare.

∗ Saab Automobile

8 VTI rapport 638A

VTI rapport 638A 9

1 Introduction The partners in the project were Saab Automobile, leading the project, VTI, SmartEye, Siemens VDO (later Continental VDO), Scania and IDA at the University of Linköping. The goal of the complete project was to develop and evaluate a real-time distraction mitigation system and to evaluate a drowsiness mitigation system in a natural setting. Due to the reason that the eye tracker used in the study had not been subjected to this kind of long-term field test before, and that the method used was quite new for all partners involved, another goal of the study was to evaluate both the equipment and the method itself. It was planned to instrument one Saab passenger car and one Scania truck with the same distraction and drowsiness warning systems. Due to delays occurring while instrumenting the Scania truck it was decided to treat the two vehicles separately. The focus of the passenger car part was on driver distraction, while drowsiness was more important for the truck study.

This report describes in detail the method used for the passenger car part of the IVSS Driver Inattention and Drowsiness project. Therefore the main focus is directed at the issues around the distraction warning system. The drowsiness warning algorithm is described, but otherwise drowsiness will not be treated within this report. For a description of the truck study the reader is referred to Kovordányi, Kolleger, Claezon and Grandlund (2009, in press).

Previously natural distraction has been studied and assessed in the field, based on video recordings and on crash databases (Klauer, Dingus, Neale, Sudweeks & Ramsey, 2006; Stutts et al., 2003; Stutts, Reinfurt, Staplin & Rodgman, 2001). Distraction mitigation systems have emerged only recently, however, and they have only been investigated in simulators. Those studies showed, however, that it was difficult to attain “true distrac-tion” in an artificial setting (e.g. Almén, 2003; Karlsson, 2005). Distraction mitigation researchers, who performed a series of experiments in different simulators recommend using a field test for further evaluation of distraction mitigation systems (e.g. Donmez, Ng Boyle & Lee, 2006; 2007; Donmez, Ng Boyle, Lee & McGehee, 2006; Zhang & Smith, 2004). It was deemed necessary to choose a setting where the driver is not disturbed by an experimental leader in the vehicle. It was also considered important to let the driver go about his or her daily routines, providing a setting that was as natural as possible. This ruled out test-track and short term studies in real traffic.

These considerations together with the maturation of remote eye tracking systems, which can be operative for a long time without experimenter intervention, led to the decision to perform a distraction mitigation test in the field, using the general methodo-logical setup of a field operational test (FOT), but on a smaller scale than common for this type of test. A detailed literature review on distracted driving with focus on methods used to assess driver distraction and on eye glance behaviour was conducted by Kircher (2007) in preparation for the study described here.

In this report a detailed description of the method used is given. At first the participants are described, then the vehicle and the data logging equipment is presented, and in Chapter 6 the experimental design is introduced. Finally an evaluation of the method used is made, together with “lessons learnt” from the study, which can be seen as practical tips for researchers interested in conducting similar studies. Detailed technical data can be found in the appendices. The results of the study will be presented in a further report (Kircher, Kircher & Ahlström, 2009).

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2 Participants Due to time and budget constraints it was clear from the beginning that the number of participants would be small. The goal was to run eight drivers, but technical problems with the vehicle causing delays entailed that only seven participants could be run. One way to deal with a small number of participants is to reduce the variance between them as much as possible in order to be able to find effects resulting from the introduction of the warning system. For a methods evaluation, however, it would be desirable to have a large variation between the participants, because this would probably cover a larger range of situations that can cause problems, which would allow a more thorough assessment of the method.

Due to the fact that distraction warning systems are quite new, and have never been assessed in the field before, it was not immediately clear in which respects drivers would need to be homogeneous to reduce the variance between them. Considering this uncertainty and the fact that many other factors like weather, lighting and possibly other outside influences would vary substantially over the course of the study it was decided to opt for the approach to select participants with varying driving patterns, but who had a number of features in common.

The main requirement for participation was high mileage, the goal was to recruit drivers who covered at least 200 km per day. The reason for that was to maximise the data acquisition in the time available for each participant. The participants should not be professional drivers, however, because there is a chance that professional drivers show qualitatively different behaviour than non-professionals, especially with respect to dealing with distraction. Further requirements were that the drivers should be at least 25 years of age, and they should have held their driver’s licence for at least seven years. This should ensure an exclusion of novices.

The remote eye tracking system SmartEye Pro 4.0 works best if the driver’s features are clearly visible, this is particularly important for the corners of the eyes and the corners of the mouth. In order to ensure good eye tracking results the participants should not wear eye glasses, they should not apply heavy mascara and should not be bearded. A beard might cover the corners of the mouth, make-up can make it difficult for the system to find the corners of the eyes, and eye glasses can be problematic, because the frame can occlude part of the eyes, and the reflections in the glasses can disturb the eye tracker. Sun glasses are particularly difficult to handle for the system.

In order to find participants that fulfilled these criteria health centres dispatching district nurses, travelling salesmen and drivers from VTI’s participant database were contacted. Participants and institutions showing interest in the study were given an information leaflet describing the purpose of the study and the requirements for participating (see Appendix 1). The project received some attention by the press, which subsequently led to interested people’s contacting VTI, wishing to participate in the study. In total one district nurse, one travelling salesman, one forest technician, two employees of two different institutes, one university employee and one doctoral student participated in the study.

The participants did not receive any monetary compensation for their efforts. They received reimbursement for fuel, however, when the experimental car consumed more than the participants’ own car. Additionally, they could reduce wear and tear on their own cars, because they used the experimental car for a month.

VTI rapport 638A 11

3 Vehicle The test car was a Saab 9-3 SportCombi Aero from 2007 with a 2.8 litre engine and automatic transmission with six gears (see Figure 1). It was provided by SAAB Automobile AB. The Saab 9-3, as well as its predecessors Saab 900 and the major model Saab 9-5 are quite common in Sweden.

It would have been preferable to choose a more environmentally friendly vehicle. It is also possible that the relatively high performance specifications encouraged drivers to exhibit behaviour that might not be typical for them otherwise. The vehicle choice could, however, not be influenced by the project partners.

The front passenger airbag was disabled for participants who had child restraints in front. Besides a visible camera behind the passenger seat the car looked just like a standard Saab 9-3.

Figure 1 The test vehicle was a Saab 9-3 SportCombi Aero.

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4 Data acquisition system The data acquisition system consists of several modules, collecting data both from the own network of the vehicle and from external sensors. A detailed description of the hardware is given in this chapter.

4.1 Power module The hardware was mounted in the spare wheel compartment. No hardware (besides the cameras and two small GPS receivers) were visible for the driver. The power system is shown in Figure 2. An important requirement was that the hardware onboard should not draw so much power to discharge the battery, furthermore the voltage had to be very stable and within certain limits. From the car battery the power was led through a control hardware in order to allow for example the computer to shut down in a controlled way when the car was stopped and the ignition key removed, furthermore functions for hard-resetting the computer were present. It is well known that certain hardware components are vulnerable to high and low temperature, as well as humidity and vibrations. For this reason additional cooling fans were installed in order to keep the temperature at acceptable levels, furthermore an active thermostat-controlled heating fan was installed to raise the temperature in cases the car was parked outside in sub-freezing conditions during the night (this was especially important for the hard disks). Humidity was controlled as well with the fans leading air out of the spare wheel compartment. In order to ensure sufficient battery capacity a second full size battery was installed in the car. Voltage spikes arising from the starting motor of the car can cause damage to the computer; these were filtered by the second battery and its protection circuits. All contacts and connectors were proofed for vibration resistance. For safety reasons no 110 or 230 Volt power was in the vehicle, all hardware was running on 12 Volt or lower voltage.

VTI rapport 638A 13

Figure 2 Power logic for the hardware. 4.2 Data acquisition hardware As mentioned the data acquisition system was mounted in the spare wheel compartment of the car, as can be seen in Figure 4. Data was acquired from different sensors: vehicle data from the CAN bus, position data from GPS sensors, video data from cameras and gaze and eye blink data from the eye tracking system. A CAN bus interface collected relevant CAN data, whereas AD-converter digitised other analogue data in the car. Besides the video recordings all data were stored via the computer (USB connections) on an external hard disk. This allowed to replace the external hard disk quickly when a new participant started to drive. The data was stored in simple ASCII files, this was seen as more robust and less resource consuming than opting for real time acquisition in a data base. The computer ran on Windows XP, algorithms and data collection routines were developed in C++.

A schematic view of the hardware is shown in Figure 3.

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Figure 3 Simplified schematic of the hardware.

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Figure 4 Data acquisition system in the spare wheel compartment. 4.3 Smart Eye Pro The gaze and eye lid-tracking system used was Smart Eye Pro 4.0, with two 8 mm IDS uEye USB-cameras fitted with band pass filters to keep interference from sunlight and other external light sources to a minimum. The face was illuminated using two NIR LED arrays mounted near each camera.

A special software update was made that enabled a re-calibration of the cameras based on the head model of the driver.

4.3.1 Hardware The long term exposure to a demanding vehicle environment and the limited power availability in the car made a regular PC with a frame grabber card and analogue cameras nearly impossible to use. Instead a light weight AOpen 12V MiniPC and uEye-1220 USB cameras were selected. The cameras were chosen because of the ability to run on USB, their durability, low power consumption and their good sensitivity in the NIR spectrum. Due to the limited bandwidth of USB, the cameras were set to run at 42Hz. The illumination and cameras were synchronised using an external processor (cf. also Figure 5).

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Figure 5 A schematic overview of the SmartEye Pro system. 4.3.2 Software Smart Eye Pro is a non-intrusive full 3D head and eye tracking system. It provides head position and rotation, a 3D gaze vector and the eyelid opening in millimetres. For a distraction and fatigue warning system, the eye lid and gaze direction measurements are most important.

The output from the system is an eye lid opening measure, in millimetres and a gaze vector originating in the middle of both eyes. A world model with various areas of interest, such as the dashboard, speedometer and windscreen is defined, and the system outputs which, if any, of the areas of interest the gaze vector intersects.

The intersections, the gaze vector and the current area of interest is then sent to the attention and fatigue detection algorithms over a UDP connection.

4.3.3 Algorithm outline A 3D head model is calculated using manually marked snapshots from the subjects face in different head poses. The snapshots also provide templates for feature tracking and larger templates for finding the face in the camera image. The head model only needs to be created once for each subject.

When a head is found, each feature point is tracked and the head pose is then calculated using the tracked positions and the previously calculated head model. For subsequent frames the previously tracked and fitted pose is used as starting points for the feature tracking. If tracking is lost, the system will go back to face finding mode until a face is found again (see Figure 6).

VTI rapport 638A 17

Figure 6 Flow diagram of the tracking algorithm.

With the 3D head pose we can find the areas where the eyes and eyelids are located. Using filtering and edge detection we provide input images to our iris and eye lid tracking algorithms. The gaze vectors is built using the position of the eye centre in the head model and the tracked positions of the iris and the eye lid opening is found by fitting an arc to the edges of the eyelids.

4.4 Mobile hard disk To allow easy handover of log data the vehicle computer stored the data on an external hard drive (Figure 7). Thus it was easily possible to replace the hard drive with a second one when the car was handed over, and between the baseline and the experimental phase, without need to copy files directly from the computer.

The requirements were:

− Small design

− Rugged, temperature and vibration resistant construction

− Large size (at least 100 Mbytes)

− USB 2.0 of IEEE-1394 connection (possible Firewire 800).

The selected model was a Hitachi Travelstar HTS421212H9AT00, 4200 RPM, 2,5´´, 120 GB.

The 2,5” enclosure was a standard model with Firewire 800, USB 2.0 and DC input connection. External power connection was not needed, as both Firewire 800 and USB carry power to the device. A second swap hard disk was available (with the same enclosure).

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Figure 7 The hard disk for log data, mounted in the vehicle. 4.5 GPS in the instrumented vehicle GPS receivers were needed to log geographical position data and give input to a digital map to record the vehicle position in real time. One receiver was used to log position data directly, the other as input for the digital road map. When the actual position of the vehicle is known, it is possible to acquire information about the road layout like the type of road, the presence of intersections, the speed limit and also about weather conditions off-line. This information allows matching situations for a more detailed analysis.


− Small design


− USB connection

− 1 HZ update rate

− SirfIII GPS chip.

The selected model was a GPS module BU-353 (see Figure 8).

VTI rapport 638A 19

Figure 8 GPS receiver.

The GPS receivers were placed close to the window on the left hand side in the rear part of the car (see Figure 9). This guaranteed both a relatively free view to the sky and protection from precipitation.

Figure 9 Placement of the GPS receivers in the car.

For logging the GPS position a custom program was developed. This program started each time the computer started and logged the GPGGA and GPRMC NMEA data sentences. GPGGA is the GPS system fix data, and GPRMC is the recommended Minimum Specific GPS/TRANSIT data. The sentences are described in Appendix 6. The logging software created a new log file each time the computer was started. Synchronization with the other log data was possible via the time information, received from the GPS satellites. The computer time was adjusted with the GPS time, too.

The raw NMEA data was converted to Keyhole Markup Language (.kml) files to view directly on Google Earth or similar digital mapping programs. A simple freeware pro-gram performed the conversion and displayed the route travelled by the participants on the digital map, complete with speed information. A sample digital map is shown in Figure 10, note that the speed of the vehicle is represented by the height of the green position dots. The street names are also visible in the map. The NMEA data can be used for other purposes as well, such as finding maximum speeds on certain road types, etc.

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Figure 10 GPS NMEA position file displayed in Google Earth.

The second GPS receiver was used to update a digital map, which was recorded via the video recorder. Microsoft Autoroute was used to display the real time GPS position. This was visualised full screen, and the video signal was directly recorded by the video logger, see figure below. The digital map was always centred around the vehicle position, which is represented by the red dot in Figure 11.

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Figure 11 GPS real time position information displayed on MS Autoroute digital mapping software.

As the video recorder can act as a web server it was planned to send the mapping data in real time, such that they could be seen any web browser or directly on computers connected via remote terminal. However, due to technical problem with the wireless connectivity of the vehicle via 3G/GSM modem this was not possible.

4.6 Digital mobile video recorder The digital video recorder stored four video inputs: computer screen, real time map (GPS position), vehicle front view, and driver.


− Digital hard disk drive recorder

− Long time recording (over 20 days)

− Full stand alone operation

− Mobile hard drive recorder, rugged construction for in-vehicle use

− Programmable settings for recording

− Possible to export videos in common format (for example avi or mpg)

− Local support (in Linköping or at least Sweden).

The selected model was a Heitel CamMobile 4 (with 4 camera inputs, see Figure 12).

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Figure 12 Digital video logger.

The space needed for recordings on the hard drive is dependent on:

− frame rate (frames per second)

− bit rate (image recording quality)

− compression technology

− number of cameras

− audio recording (yes or no)

− colour or b/w image

− content of image

− duration of recording.

In the present field test the 120 GB hard disk was sufficient for recording typical driving during the baseline respectively treatment phase. A second hard disk was available in order to allow for fast replacement when needed. Usually the hard disk was replaced during the shift from baseline to treatment phase. A USB enclosure allowed to connect the hard disks to a computer.

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Figure 13 Video recording, actual example from test drive (driver’s face blurred for anonymisation purposes).

It was possible to jump directly to special pre-defined events in the videos, for example a distraction warning. On the upper left hand screen of the quad screen the outside scene in front of the car was visible, on the upper right hand screen the driver was filmed over the shoulder, on the lower left hand screen a map of the surroundings with the current position and a trace was shown, and on the lower right hand screen the view of the two eye tracker cameras, the drowsiness status as judged by the algorithm and the inattention and drowsiness monitoring display were shown (see Figure 13). The display is described in more detail below.

The recording frequency and the disk space distribution for the four different views can be found in Table 1.

Table 1 Recording frequency, disk space distribution and available continuous recording time for the video logger.

camera target percent disk space allocated

recording frequency

available continuous recording time

camera 1 outside scene 27% 5 Hz 1w5d camera 2 cabin 38% 5 Hz 1w5d camera 3 gps 20% 2 Hz 1w6d camera 4 display 15% 1 Hz 4w

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4.7 VGA-FBAS video converter In order to record the computer video signal in the digital video recorder a VGA-TV video converter was used.


− Small design


− Supported resolution minimally 1280*1024 pixels at 50 Hz

− to 12 V power supply

− FBAS compatible video output.

The selected model was a Grand Hand View II VGA to TV converter (see Figure 14).

Figure 14 VGA to TV video converter. 4.8 Camera for driver monitoring A camera to monitor the driver was installed above the right back seat. The view is visible in Figure 13. A camera with IR LEDs for night use was found to disturb the system, as mechanical relais control the IR lights (audible to the driver each time IR is switched on), furthermore the camera registered the IR light from the eye monitoring cameras. Thus a high sensitivity camera without IR lights was used. The camera is able to work at night time.


− Small design


− FBAS video output, 5, 6 or 12V operation

− High resolution and light sensitivity

− Lens with variable zoom.

The selected model was a Watec WAT-902H (Figure 15).

VTI rapport 638A 25

Figure 15 Camera for driver monitoring.

For safety reasons the mounting of the camera had to be secure enough to avoid loosening even in case of an accident. A passenger seated on the back seat on the right hand side should not be able to move the camera, rotate lenses or disconnect cables.

The camera was mounted behind the passenger seat under the roof of the car (see Figure 16). It afforded a view of the driver’s body and hands from over his or her shoulder (see Figure 17).

Figure 16 Placement of the cabin camera under the roof of the car behind the passenger’s head rest.

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Figure 17 View of the in-car camera observing the driver. 4.9 Monitor, keyboard, mouse A standard computer keyboard and mouse were used. The monitor was a 12 V operated TFT 17” screen, with option to connect VGA and FBAS video. This allowed to connect the computer and to control the camera outputs directly. Computer, keyboard and mouse were only installed when the experimenter met the participant, not while a participant was driving it during the baseline and the experimental phase.

4.10 Network It was planned to connect the vehicle’s computer to a network accessible via standard 3G or GPRS services, this was not possible due to technical problems. A standard network switch was installed, which connected video logging equipment, computer, and 3G modems. Furthermore a remote desktop application allowed using the car’s compu-ter via a desktop client.

4.11 Audio mute box In order to disable the audio warning messages manually during the base line drive a mute box was installed, which muted the audio input to the speaker. The mute box had a simple switch which operated a relay to disconnect the audio input to the speaker.

4.12 Software The computer ran on Windows XP SP2. The software system developed for the project consisted of several separate console programs written in standard C++ using distribu-ted software architecture (figure 1). The modules were compiled into separate execu-table binary files and communicated with each other using a UDP peer-2-peer network library called INet, which enabled scalability and possibility to share CPU load over several computers. UDP is often preferred in time sensitive applications as it is much faster and dropped packets are preferable to delayed packets, but it also implies careful consideration of data integrity due to this. This was handled with a ring ordered numbering of the data packets sent and every receiver raised an error flag if this

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ordering was broken. The network library acted as a gateway and translator of messages between the different communication standards used by the eye tracking software, the vehicle CAN bus, the I/O card, and the drowsiness detection system. Each data signal from the different modules was translated into a common set of signals, which in turn was available for all modules running on the local network. During the iterative process of developing the inattention algorithm some of the signals were simulated by Saab Driving Simulator, creating a real time test bench mixed with real and simulated values.

Figure 18 A schematic overview of the distributed architecture. 4.12.1 Configuration files XML files were used to enable easy configuration during the design phase. Each module had one configuration file describing its INet communication settings in terms of module names and port settings. The modules had several individual files which were algorithm specific and were used to tune the different algorithms during the test phase. Some of the configuration files were altered during the experiment to handle the difference between the baseline period and the period when warnings were activated.

4.12.2 Data logging The data logging functionality was distributed between all the modules and every input- and output signal was written to one ASCII file per module. The data were logged in a pre-determined frequency and each variable was upsampled to the highest working frequency of the module. Each log row was marked with a common time stamp, enabling synchronisation of data in the analysis phase. The upsampling was made on non time critical values not affected by distortion, while time critical values as eye tracking data and algorithmic output were logged in its original frequency. Apart from raw data input and algorithmic data, each module also logged special events as fault codes, inhibited warnings etc. The data logging algorithm had its own thread inside of each module, working in parallel with the main function utilizing thread safe message passing methods.

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4.12.3 DrowsyServer This server application was responsible for the communication between SDM, Siemens Drowsiness Module and the rest of the system. The SDM application was implemented by Siemens VDO and had a socket communication with a simple API for sending and receiving data to the server application (Figure 18). The server application provided eye tracking data to SDM from SmarteEye Pro at a rate of 42 Hz, and drowsiness output on INet from SDM at a rate of one new value every 30th second.

Figure 19 API overview for SDM client and server communication. 4.12.4 Inattention Decision Program The Inattention Decision Program implemented the inattention algorithm described in section 5.2. The main inputs for this program were eye tracking data from SmartEye Pro and vehicle data from the CAN bus.

4.12.5 I/O Controller The I/O Controller program communicated with a USB connected Input/Output device. The I/O device had 8 digital output ports and 8 digital input ports. The output ports were connected to the haptic motors which were used to warn the driver for inattention, to the Power Module for the required I/O pulse and to the video logger for annotation of special events. The input ports were used for the drowsiness acknowledge button which the driver pressed to confirm a drowsiness warning.

4.12.6 SmartEye converter SmartEye Pro uses either UDP or TCP protocol to send its data to third party programs. Here the UDP settings were chosen and SmartEye Converter converted the received UDP data into INet data at 42 Hz.

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4.12.7 Information display The program was developed to give a real time visual representation of the system and its internal states. This was extensively used during the design phase and provided a powerful tool for developing the warning strategies. The program used openGL for fast drawing of data and statistics. See section 5.8 for more details regarding the Information Display.

4.12.8 CAN_Inet The program monitored signals on the vehicle CAN bus through a USB connected CAN interface and forwarded them onto INet in combined packets. The signals were in some cases scaled and an offset was added to the original value. The selection of signals to be monitored were carefully chosen and configured through an XML configuration file. The program used a development library from Vector (Vector Informatik GmbH, Stuttgart, Germany), the company providing the CAN interface hardware.

4.12.9 Warning control The program gathered all available information on INet and used rules to decide whether to warn and how to warn the driver at each given moment. The rules were based on simple if-then-else logic and fully configurable with three XML files.

<!‐‐ Speed is too low ‐‐> <Rule name="Low Speed"> <Speed lower="1" higher="0" equal="0">50</Speed> </Rule>

The above code snippet shows an example rule, which says that a warning should be filtered if the speed is lower than 50 km/h. See section 5.6 for more information regarding inhibition of warnings.

4.12.10 WinPos This program moved every module into its correct position on the two screens connected to the computer. This precaution was made to ensure that the video data looked the same and that nothing got obscured by an irrelevant dialogue window.

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5 Inattention and drowsiness detection system The inattention and drowsiness warning systems were both based on real time eye tracking data, which were provided by the SmartEye system. Otherwise, both systems worked independently of each other. The drowsiness detection algorithm was developed by Siemens VDO, later Continental Cooperation. The distraction warning algorithm was developed jointly by Saab Automobile and VTI.

5.1 World model car The car is subdivided into 15 different zones, which are the windscreen, the right front window, the left front window, the right rear view mirror, the left rear view mirror, the centre rear view mirror, the dashboard, the speedometer, the middle console, the glove box, the left front door, the right front door, the floor of the car, the foot area and the roof. Zones behind the driver’s seat are not defined, because glances of the driver behind this line will not be picked up by the eye tracker and recorded as lost tracking instead (Figure 20).

Figure 20 The world model of the vehicle, seen from behind the driver. The white rectangles determine the different defined zones, which were used for the algorithm. The green circle shows the position of the head. The yellow dots demarcate the cameras. The red line from the head through the windscreen indicates gaze direction, the blue dot indicates the intersection point between gaze direction and windscreen.

As long as the driver’s gaze is directed through one of the windows and not at the mirrors and lies at the same time within 90° forward, the driver is considered to be

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looking at the “field relevant for driving” (FRD, see Figure 21). The rear-view mirrors and the speedometer are outside the FRD, but they are not considered to be completely irrelevant for driving. The literature indicates that the mean duration of glances to these targets is approximately 0.6 to 1.0 s (see e.g. (Kircher, 2007)). For the present study it was decided not to assume that the driver is attentive when he is looking at the those targets for the duration of one second or less, in order to account for the safety relevant aspect of checking the mirrors and the speedometer briefly. Prolonged glances of more than one second will, however, lead to the assumption that the driver is inattentive.

Figure 21 The ”Field Relevant for Driving” as seen from above, provided that the driver looks through a window.

Glances at all other zones lead to the immediate assumption that the driver is not attentive to driving at the moment. These assumptions are the foundations for the inattention detection algorithm, which is described in more detail below.

5.2 Inattention detection algorithm One task within the project was to develop a distraction detection algorithm based on the initial work done by Almén (2003) and Karlsson (2005) supported by Saab Automobile. So far the algorithms that were found in the published literature (Donmez, Ng Boyle & Lee, 2007; Victor, 2005) were not deemed to be validated enough to be seen as a promising candidates for the present project. An algorithm based on a world model of the vehicle was assumed to be more exact than more general approaches.

The distraction detection algorithm developed here is based on the notion that both long single glances and repeated glances are detrimental to traffic safety. This is documented extensively in the literature (e.g. Kircher, 2007; Lee, McGehee, Brown & Reyes, 2002; Tijerina, Parmer & Goodman, 1999; Tsimhoni, 2003; Wikman, Nieminen & Summala, 1998).

For the algorithm it is assumed that the driver has a buffer of two seconds which can be spent looking at targets outside the field relevant for driving. Two seconds were chosen, because this value is often cited as critical for single glances (for a summary see Kircher, 2007). Additionally, in the 100-car study it was shown that accumulated glances away from the forward roadway of more than 2 s within a window of 6 s led to an increased crash risk (Klauer, Dingus, Neale, Sudweeks & Ramsey, 2006).

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When the attention buffer is empty, the driver is considered to be visually distracted. The buffer is filled when the driver looks at the FRD and decreased when the driver looks at other targets, according to the rules described in the following sections. Warnings are given when the driver is considered to be distracted and a number of other pre-conditions are fulfilled, that are described further down.

When the driver looks at targets that are completely irrelevant for driving safely, like the radio, the glove box, the car floor, etc., the buffer is decreased immediately with a factor of one, that is, for each second spent looking at something outside of the FRD, the buffer is decreased with one second. This way, a glance outside of the FRD that lasts for two seconds leads to a warning when no inhibition is active.

While driving it is important, however, to check both the speedometer and the rear-view mirrors. This was shown empirically with data from the 100-car study, that predict a lower crash-involvement for drivers that scan the mirrors and the speedometer (Klauer, Dingus, Neale, Sudweeks & Ramsey, 2006). The average glance duration to mirrors and speedometers lies at around 0.8 to 1.2 s, with minor variations between targets and studies (for a summary see Kircher, 2007). For the present algorithm it was decided to allow glances to the mirrors and the speedometer that last for one second before the attention buffer is decreased. It was assumed that the average glance duration to those targets reflects the time that is needed to obtain information that is relevant for driving. One second was chosen as an approximate average of the values reported in the literature. During this second, while the glance rests on one of the mirrors or the speedometer, the attention buffer remains at the current level. Longer glances to those targets, however, are assumed to be unnecessary and an indication of visual driver distraction. Therefore, the attention buffer is decreased with a factor of one as soon as the glance time to the mirrors or the speedometer exceeda one second.

When the driver looks back to the FRD, the buffer is increased again, also with a factor of one. There is, however, a 0.1 s latency phase, in which the buffer remains at the current level, before the increase is initiated. This latency phase is meant to reflect the adaptation phase of the eye and the mind to the new focusing distance and the driving scene. As soon as the driver looks away from the FRD again, the buffer is decreased again. Thus three glances of one second each would lead to a curve like the one in Figure 22.

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0 s-1 s-2 s-3 s-4 s-5 s-6 s-7 s-8 s-9 s

buffe

r

0 s

2 s

glance to FRDglance away from FRDglance to speedometer/mirror

time Figure 22 Representation of the development of the attention budget for three conse-cutive one-second glances away from the field relevant for driving, marked red, with half-second glances back to the field relevant for driving in between. Between -1.8 s and 0 s a 1.8-s-glance to the mirror or speedometer is shown.

Starting from the left, which is ten seconds into the hypothetical driver’s past, the driver has a full attention buffer. About 8.75 s into the driver’s past he looks away from the FRD for one second, indicated by the red bar. The buffer is decreased with one second. When the driver looks at the FRD again, which is indicated by the white bar, a 0.1-la-tency-period passes before the buffer is increased. Then the driver looks away from the FRD again, and so on. At 5 s into the driver’s past the buffer is empty. When no inhi-bition is active, the driver receives an inattention warning. After having received the warning 0.4 seconds pass until the driver looks at the FRD again. His next glance away from the FRD is at either a mirror or the speedometer, indicated by the green bar. There-fore the buffer is not decreased immediately, but first after one second has passed.

If eye tracking is not available, but head tracking is still possible, the algorithm is based on the “nose direction” of the driver. If the driver’s nose is directed at a point within 90° forward and higher up than 22.5° downward, the driver is assumed to be attentive. Also here the latency phase for buffer increase is 0.1 s and the increase factor is one.

If tracking is lost completely, the attention buffer change depends both on the buffer value and the head direction angle at the time when tracking is lost. If the buffer value lies below 0.4 s when tracking is lost the buffer is decreased further with a factor of one. If the buffer lies above that value it remains at its current value in case that the head direction angle when tracking was lost was within 20° of forward. If the head direction angle lies outside of this value the buffer is decreased with a factor of one.

For the present study it was decided to settle on the 15 zones named in Chapter 5.1. A subdivision of the vehicle world model into too small zones would not necessarily increase accuracy, because the eye tracking system is not that accurate especially in the zones that are far away from centre forward. No results with respect to eye tracking accuracy based on automatic gaze direction tracking were so far reported for studies of longer duration. For the present study a first evaluation of the eye tracking quality with respect to glance direction is reported in Kircher, Ahlstrom and Kircher (2009, submitted).

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5.3 Distraction warning The distraction warning consisted of a vibration in the driver’s seat. Four actuators were integrated into the driver’s seat. Two were positioned in the frontal part under the driver’s legs, and two were placed in the rear half of the seat, slightly further to the sides. When the attention buffer reached zero and no inhibition was present, all four actuators started vibrating at the same time. The vibration could easily be felt both on asphalt and on gravel roads. The vibration stopped when the driver looked to the “field relevant for driving” again, or at the latest after two seconds.

Before settling on this solution, different other approaches for warning the driver were discussed. Visual signals were excluded, because a visually distracted driver might not notice a visual cue. Additionally, it was deemed to be important to only inform the driver, but not the passengers, about the occurrence of driver distraction. Therefore, auditory warnings were excluded, too. Both a vibrating seat and a vibrating seat belt were seen as viable alternatives. Especially due to the fact that a truck with the same instrumentation should be run in parallel, it was finally decided to opt for a vibrating seat, as truckers are known not to wear the seat belt as frequently as passenger car drivers do. A vibrating seat was considered to be able to reach practically all drivers, regardless of how distracted they were.

5.4 Drowsiness warning algorithm The main contribution of Siemens/Continental VDO to the study was the provision of the drowsiness warning algorithm. This decision had been made before the project was started. During the planning phase of the project no other alternatives to this warning algorithm were discussed.

The drowsiness warning strategy uses the eyelid motion signal in order to provide an on-line diagnostic about the driver state.

This algorithm includes two main steps:

o The blink detection and classification

o The diagnostic that’s provide de various warning levels.

5.4.1 Blink characteristic parameters A typical spontaneous blink for an alert person presents 3 phases (see Figure 23).

o a closing phase (the eyelid goes down)

o a closed phase (the eye is shut)

o an opening phase (the eyelid goes up).

Short Blink Long Blink

400 ms

200 msOpen

Closed

OpeningClosed

Closing

Amplitude

Figure 23 Typical shape of blinks.

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The closing phase of a normal blink is shorter and faster than the opening phase; it takes about 60 ms with a maximum velocity of approximately 350 mm/sec. The opening phase takes about 120 ms with a maximum velocity of 150 mm/s. The maximum velocity and durations of eyelid closing and opening do not depend on the starting lid position. A typical blink duration of an alert driver is around 200 ms. Drowsy drivers exhibit long blinks (typically above 300 ms) while drivers getting sleepy can exhibit very long blink (typically above 600 ms).

The blink amplitude of an alert person, with eyes wide open, is characterised by a maximum value of 10 mm. The amplitude can be much lower for some eye morpho-logies or also during day driving conditions when the driver partly closes his/her eyes to reduce the light input.

5.4.2 Blink detection The objective of the blink detection algorithm is to detect the blinks to measure their durations and of course to reject artefacts as looking at dashboard patterns.

The blink detection process looks for specific patterns within the given eyelid signals. The opening signal is processed first to determine an open eye reference (base line). A transition from the upper part of the base line to the lower part is then considered as a start of the closing phase of a potential blink. Finally various shape criteria are applied to decide if a potential blink is a blink. The following main criteria are applied:

Steepness of the closing and opening phase: Each phase must last at least 3 samples.

Minimal blink duration: A blink is rejected if its duration is lower a given threshold (in ms).

Maximal blink duration: To take into account as much as possible very long eye closure the maximal duration is set to a max threshold.

A minimal and maximal Amplitude: of respectively 5 pixels and 20 pixels are considered.

Symmetry: The test of symmetry compares the opening values of the eyelids at the beginning, the end and for the minimum of the blink signal. The blink is rejected if the ratio of the higher edge of the blink and the lower edge is higher than a fixed threshold (typical value is 20%).

Figure 24 Results for the test of symmetry.

The drowsiness warning algorithm delivered a new classification of the drowsiness state of the driver every 30th second. Four different levels of driver state exist (see Table 2).

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Table 2 Different levels of driver drowsiness as determined by the drowsiness warning algorithm.

level driver state

0 alert driver

1 slightly drowsy driver

2 drowsy driver

3 very drowsy driver

In order to reduce the likelihood for false alarms, which can occur for example when the driver is squinting due to sun glare, an “oscillation avoidance algorithm” was applied before sending a warning to the driver. This implies that in order to obtain a warning on a certain level above 0, this level or a level above needs to be delivered at least twice within five consecutive state classifications. As soon as a lower level was reported, the driver state classification was reset to this level, however.

5.5 Drowsiness warning The drowsiness warning was given in three stages related to the current drowsiness classification. On each classification level the driver had the possibility to press a confirmation button, acknowledging the warning (see Figure 25). This led to a delay for the next warning on the same level, in order to allow the driver to find a suitable loca-tion to rest. The drowsiness classification of the driver, the resulting warning, and the consequences when the driver presses the confirmation button are described in Table 3.

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Table 3 The drowsiness classification of the driver, the resulting warning, and the rules for the repetition of the warning.

display sound repetition

level 0 (alert)

level 1 (slightly drowsy)

“Trött?”

“Drowsy?”

discreet beep message disappears after 15 seconds and appears again after 30 min at the earliest if the same drowsiness level is present

button pressed: message disappears immediately, and appears again after 30 min at the earliest if the same drowsiness level is present

level 2 (drowsy)

“Du är trött”

“You are drowsy”

discreet beep

voice: “Du är för trött för att köra!”

”You are too tired to drive.”

beep and voice message repeated once per minute as long as same drowsiness level present

button pressed: text and voice message presented again after 5 min at the earliest if the same drowsiness level present

level 3 (very drowsy)

“Du somnar snart”

“You will fall asleep soon”

loud beep

voice: “Du är farligt trött! Stanna snarast!”

”You are dangerously tired. Stop soon!”

beep and voice message repeated once per minute as long as same drowsiness level present

button pressed: text and voice message presented again after 5 min at the earliest if the same drowsiness level present

A supplemental speaker was installed to output the audio warning messages. Ideally this would have been integrated into the vehicle audio system. The speaker used was a standard active computer speaker (mono operation) with direct input from the vehicle computer. It was mounted behind the rear seat line. The same safety consideration as for the camera for driver monitoring applied here.

The car had no built-in display, therefore a VFD/LCD-display was mounted in the cockpit. The display was connected via USB and was controlled by the Warning Control Program. ELFA had a suitable LCD or VFD display with 2*20 characters (Swedish Alphabet supported). The display was USB-controlled and measured 98 x 60mm. The display required some wiring, an enclosure and a mount.

It was decided to choose both visual and auditory warnings for the drowsiness system in order to include some redundancy, especially on the more severe drowsiness levels. It was also seen as an advantage if possible passengers realise that the driver is critically drowsy, because they might influence the driver to take a rest. Furthermore, it was decided not to use the same mode for the distraction and the drowsiness warning system, such that they could be completely separated from each other. Therefore, no haptic warnings were issued for the drowsiness detection system.

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Figure 25 Participant presses confirmation button (photo: Tedd Soost). 5.6 Inhibitions In order to avoid false alarms the warnings were inhibited under the conditions described in Table 4. This means that the warnings were registered in the logfiles as inhibited warnings, but they were not sent to the driver. Most inhibitions applied for both the distraction and the drowsiness warning system, some where specific for only one of the systems.

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Table 4 Inhibition criteria for drowsiness and distraction warnings.

variable threshold motivation

speed < 50 km/h (inattention) Below 50 km/h gaze behaviour is not very uniform. The gaze is often outside the FRD without the driver’s being distracted.

< 5 km/h (drowsiness) Drowsiness warnings are inhibited below 5 km/h in case that the driver remains in the seat with engine on to take a nap – no drowsiness warning should be given in that case.

direction indicators on Changing lanes and turning can include planned glances outside the FRD.

gear reverse Reverse engaged means that the driver should look over the shoulder.

brake pedal pressure above 75 No warning should be given while driver is braking, in order not to interfere with critical driving manoeuvres.

For the Saab the brake pressure is measured in 75-kPa-steps. Because vibrations can cause the sensor to show 75 without the brake being pressed, the threshold is set above 75.

steering wheel angle

> 20 for speeds 50-90 km/h

> 10 for speeds > 90 km/h

No warning should be given while the driver is engaged in substantial changes of direction, in order not to interfere with critical driving manoeuvres.

StwAngle depending on speed.

lateral acceleration > 5 m/s2 No warning should be given when the vehicle makes strong movements, in order not to interfere with critical driving manoeuvres.

5.7 Manual Each driver received a user manual describing the distraction and drowsiness mitigation system after having completed the baseline phase. The manual was placed in the car for reference. The participants were informed about the existence of the manual, but they were not specifically instructed to read it. A copy can be found in Appendix 5.

5.8 Display One of the four displays on the quad screen showed some statistics of the current trip. This information is an aggregation of the text log data and is mostly meant to help the viewer of the video recording to get a better picture of the trip history. It was also used

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extensively during the development phase of the distraction detection algorithm, and during test runs when the data acquisition system was monitored for correct performance. During the study phase the monitor that showed this display was disconnected and removed from the vehicle.

14:12:16,20 01:42:21,60 81.3 %

73.5 % 98.9 %1030507090110130150

Figure 26 Schematic picture of the data sector of the fourth field in the video logger.

The left hand side of the picture provides continuous information on some variables, and some additional information. The four boxes on the right hand side provide some histogram information, but also some continuous information. In Table 5 the informa-tion in the figure is explained.

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Table 5 Explanation of the symbols and graphs in Figure 26.

variable description

time of day The timer on the upper left hand side.

duration of trip

The timer on the right hand side.

direction indicators

The boxes in the upper corners of the left field, the left one is currently orange, i. e. “on”. Whenever a direction indicator is on, the corresponding field is illuminated.

This info provided because direction indicators are warning inhibitors.

speed The thick black line on the left hand side documents speed over the last 10 s. The most recent value is on the right side of the diagram.

The displayed speed range goes from 0 km/h to 150 km/h. The first reference line lies at 10 km/h, and then with 20 km/h difference upwards (“odd” numbers are used due to the Swedish speed limits, which most often lie at 30, 50, 70, 90 and 110 km/h).

drowsiness algorithm

The thin blue line just below the timers indicates the current drowsiness level, as presented to the participant. No colour means “alert” (level 1), light blue means “slightly drowsy” (level 2), middle blue means “drowsy” (level 3) and dark blue means “almost asleep” (level 4).

drowsiness history

The last six drowsiness levels are colour coded in the lower right hand corner of the graph (fourth quadrant); grey meaning alert, from light blue to dark blue increasing drowsiness, the confidence level is coded by either a red cross (0) or no red cross (1). Thus, the last 3 minutes of drowsiness estimation are visible, the most recent is furthest to the right.

drowsiness warning

The blue line reaching down from the drowsiness algorithm indicator marks a drowsiness warning. Repeated warnings look similar. Colour coding similar to “drowsiness history” and “drowsiness algorithm”. For an inhibited warning the colour coding is grey.

drowsiness warning count

The histogram in the fourth quadrant on the right side of the display counts drowsiness warnings for each level separately. Repetitive warnings are counted, too. For the black parts of these boxes refer to “drowsiness acknowledge count”.

The percentage of time which the driver has been alert up to the current time is presented as clear text in the same quadrant. In the example presented here the driver has been alert 98.9% of the time on this trip.

drowsiness acknowledge

The black line coming down from the drowsiness algorithm indicator marks the press of the drowsiness acknowledge button.

drowsiness acknowledge count

The black box within each drowsiness warning count bar in the drowsiness quadrant counts how often the drowsiness acknowledge button was pressed for each separate level.

data loss blink

The separate black bar in the drowsiness quadrant indicates the percentage of data loss for blink data for the whole trip.

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Continuation of Table 5.

inattention algorithm

The graph underneath the speed graph on the left hand side of the display shows continuously how the time budget developed over the last 10 s, the most recent value appears on the right side. The “height” of the value indicates the status of the time budget, the history allows to judge whether it is increasing, decreasing or stable. The range is from 0 s to 2 s.

The inattention algorithm result (y-value of the graph) is indicated no matter which data quality level is presently used (also for data loss situations).

glance quality The glance quality is colour coded in the attention algorithm display. As long as eye tracking is present, the graph is green, when only head tracking is present the graph is grey (data loss is black, see below under “data loss glance”).

data loss glance

The separate black bar in the inattention warning count quadrant indicates the percentage of data loss for glance direction for the current trip (the grey field indicates presence of head direction tracking, but loss of eye direction tracking).

inattention warning

The red bar going up from the inattention algorithm display indicates that an inattention warning has been issued to the driver (when the time budget reached 0 s). The width of the bar indicates how long the warning was “on”. Inhibited inattention warnings are colour coded grey.

inattention warning count

In the first quadrant (on the right side of the display) an inattention warning count is displayed. The grey count are inhibited warnings, the red count are issued warnings.

Inhibited warnings are counted when a warning would be issued, but the inhibition algorithm stops this warning from being presented to the driver (if the reason for the inhibition is not “baseline driving”; on the display both baseline and experimental phase are treated alike).

eyes off FRD The lowermost display on the left hand side displays glance direction. As soon as the driver’s glance is registered elsewhere than on the FRD this is colour coded. Data loss is indicated in black (or cf. data loss indication for inattention algorithm display). One colour coding (green) for fields that are outside FRD but driving related (mirrors, speedometer), another colour (red) for everything which is not driving critical (e.g. stereo, etc.). Side windows are treated like mirrors and speedometer in colour coding (corresponding to the treatment in the algorithm).

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Continuation of Table 5.

long glances count

The second quadrant on the right side of the display shows a “long glances count” histogram based on the glance direction (as used in the “eyes off FRD” field). Each glance above a certain duration is counted. The colour coding of the bars corresponds to the colour coding in the “eyes off FRD”-field furthest down in the left display.

The percentage of glances off FRD that are shorter than the critical values presented here as histogram bars is given in clear text in the same quadrant. The total percentage of glances away from the road per trip is not given on-line.

Borders for glance durations: .8 s; 1.2 s; 1.6 s; 2.0 s; 2.4 s; 2.8 s.

One count for one crossing of a critical border (obviously only border crossings with increasing values). All border crossings are counted, i.e. a glance of 2.6 s will count in all bins underneath as well.

Long glances are not counted when the speed equals zero.

2 in 6 count The quadrant in the lower left hand corner of the right part of the display shows data related to the “accumulated 2 s off FRD” notion as suggested by VTTI. The counts are either “border crossings” on their way up or “spot counts” 6 s after a border crossing if the value is still or again above the critical level.

The percentage of glance-off-FRD time within 6 s intervals that lies underneath the lowest critical value indicated with histogram bars is presented in clear text in the same quadrant.

Borders 2 s, 3 s, 4 s, 5 s. Whenever one border is crossed it cannot be incremented again within the next 6 s. After 6 s the value is compared to the border again, and if it is (still or again) higher than the border in question, another increment is made and the increment inhibition time set to 6 s.

2 in 6 accum. display

The lower part of the field (the horizontal yellow bar) indicates which accumulated percentage of the past 6 s window (full length of the horizontal bar) the driver has looked away from the FRD. Black indicates the amount of data loss in the last 6 s. For getting an impression of how the glances are distributed across the last 6 s view the “eyes off FRD” field from “now” until the yellow line, which indicates “6 s ago”.

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6 Experimental design and procedure In this chapter the actual experimental procedure is described. In the first section alter-natives are discussed and motivations for the current approach are given. In the sub-sequent sections the procedure is described chronologically, and special occurrences are taken up in the last section of this chapter.

6.1 Considerations about the chosen procedure Budget restrictions and the project time frame allowed to run participants within about ten months, including the pilot. It was assumed that about two days would be needed to get used to the vehicle, and another two days to get used to the warning system. In order to be able to assess the effect of the warning system, a baseline phase with the system running in silent mode, and a treatment phase with the warnings activated was necessary. It was discussed whether all participants should be subjected to the same order of the phases – first baseline (A) and then treatment (B) – or whether other designs like BA, ABA or even ABAB should be employed. The more complex designs comprising of more than two phases were ruled out due to time constraints. It was deemed important to let the participants drive for a longer contiguous time without interruptions from the experimenters’ side in order not to remind them too often about being monitored. On the other hand, it appeared difficult to let a single driver have the car for more than a month in total, because that would reduce the number of participants too much. Eye tracking quality is partly depending on the individual’s features, the longer one single participant would drive the car, the more impact on overall data qua-lity one participant with suboptimal tracking would have. Employing an AB design for half of the participants and a BA design for the other half would help controlling for possible carry-over and learning effects. On the other hand, it was considered important that during the baseline phase the participants were not aware that driver distraction was one focus topic of the study. Giving them this information might have affected their glance behaviour during baseline driving, because they might have become self-conscious about where they looked.

The treatment data should be maximised while at the same time enough data for a robust baseline had to be collected. In similar setups it was common to use one week of baseline driving and three weeks of treatment driving (Ervin et al., 2005; LeBlanc et al., 2006), but in those studies the number of participants was much higher, thus, the absolute amount of baseline data was larger due to this. For the present study a compro-mise was made – it was decided to assign one third of the driving time to baseline and two thirds to treatment, considering that two days of each phase would be omitted from the analyses in order to eliminate the period during which the drivers adapted to the vehicle respectively the system.

The final decision was to let every participant drive the car for approximately one month, with about 10 days baseline and about 20 days treatment driving, and to opt for eight participants, allowing some time for piloting and for servicing the vehicle in between the participants.

In the end only seven participants could be run, partly due to the fact that the vehicle itself had technical problems which had to be fixed in between participants, and partly due to the data acquisition system that started to become instable while the last two participants had the car. It was tried to repair the system without success, and

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replacements of major parts were deemed to be too costly and not worth the effort for running one more participant.

It was discussed whether the participants on which level of detail the participants should be informed about the warning systems present in the car. There is a large span from giving only very sparse information, as would probably happen had the participant bought the car from a dealer, or to give very detailed information with demonstrations and so on. In the current project the latter approach was chosen, partly because it was considered an advantage if it was ascertained that all participants had received similar information about the warning systems, and partly because it was easier to live up to the ethical requirements of informed consent. So far no real distraction warning systems are on the market, and drowsiness warning systems only started to be launched, therefore it cannot be expected that drivers would know the functionality of those systems, had they only been mentioned and the rest left to the driver to figure out.

The participants selected themselves in which environment they would drive, but the selection of the participants could, in turn, determine partly where and when they would drive mainly. It was opted to cover both motorway and rural road driving, whereas it was planned to avoid a large number of short inner-city trips. Those trips contained several disadvantages, because they did not generate many distraction warnings, as the warnings were inhibited under 50 km/h, and they drained the battery powering the data acquisition system and the car, because of the frequent shut-downs of the log system. Furthermore, short trips required the computer to start and shut down often, putting extra stress on the log system. Due to these reasons mainly drivers who reported them-selves that they usually took longer trips were preferred to inner-city drivers. No parti-cular selection was made as to whether the participants mostly drove during the day or during the night. Due to the large differences in daylight during summer and winter in Sweden it was assumed that ample data both from daylight and night time driving would be available in the end of the study, whose data collection period lasted from September 2007 to June 2008.

6.2 Pilot Before the first participants were run both an internal and an external pilot study were conducted. During the internal pilot the experimental leader used the vehicle as her own over the summer, both to get thoroughly acquainted with the data acquisition system, with the warning systems and with the vehicle in itself. During this pilot many smaller problems were encountered and solved. When the vehicle was considered to be fully prepared for the study it was given to an external pilot participant who underwent the same procedures as the regular participants, except that the driving period was shortened to four days baseline and eight days treatment driving. The pilot participant was questioned extensively both about his experiences with the car and the warning systems, and whether he was comfortable with the general procedure. As compensation for his efforts the pilot was paid in full for the gasoline costs that he had during the trial period. Based on the pilot participant’s comments a few minor adjustments were made before the first regular participant was invited.

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6.3 Initial contact Those drivers that had shown interest in participating in the study were contacted about two weeks before their trial started. A convenient meeting point and a meeting time were arranged. The day before the meeting was confirmed. In some cases the partici-pants were picked up, in other cases they arrived at VTI (the test centre). In any case the participant had opportunity to drive the test car and get a first feeling for it. During that time the participant was also asked to adjust the seat and the mirrors such that the parti-cipant felt comfortable. The position of seat an mirrors were saved, and the participant was asked to try to drive in this position as much as possible as long as it was com-fortable.

In order to prepare a profile for the eye tracker a film or photographs had to be taken of the participant seated in the car via the eye tracker’s cameras. The participant was asked to look straight ahead, then to keep the head in this position and turn the eyes to the left camera and then to the right camera. Afterwards the participant should look out of the left window and slowly turn the head to look out of the right window. During this time the participant should not talk or grimace. The film was saved on a portable hard disk which was then taken to the experimenter’s office, where a tracking profile was created. When photographs were taken directly, the profile for tracking was created on the computer located in the experimental car.

In the meanwhile the participant was offered a coffee. He read and signed the informed consent form (see Appendix 3) and a form assuming liability for speeding and parking tickets (see Appendix 2), etc. He then proceeded to filling in a short questionnaire about driving habits (see Appendix 4). In the meanwhile the experimenter prepared the profile for the eye tracker. The participant also received a form that should be filled in case of a crash.

The first two participants were asked whether they would agree to have an Actiwatch on their wrist during the period of the trial. An Actiwatch is an accelerometer of approxi-mately the size of a wrist watch, which logs continuously whether the arm to which it is attached is in motion or resting. From these movements it can be determined whether the bearer of the device was awake or sleeping. The first participant agreed reluctantly to wear the device, the second participant returned the Actiwatch without having used it much when he came back after the baseline period. Then it was decided that the Actiwatch would not be used on the following participants.

When the profile for eye tracking was ready the participant was asked to sit in the car. First the profile was checked while the vehicle was standing. The participant was asked to look out of the windscreen, to look at the rear-view mirrors and the speedometer, and to look at the middle console. When the profile worked satisfactorily a short test route was driven with the experimenter in the back. The experimenter gave directions and monitored the different programs on the computer screen to ensure that all modules worked properly. When this was the case the participant drove back to the test centre and the experimenter unplugged the monitor, key board and mouse and removed them from the car.

The participant and the experimenter scheduled a meeting approximately ten days later, when the warning system was supposed to be switched on. The participant also received a phone number which he or she should ring in case that problems occurred with the car. The phone was meant to be on stand-by and reachable 24 hours a day, and the number was reserved for the participants only.

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When the participant did not have any further questions he or she left the test centre with the car. The experimenter archived the forms and questionnaires and assured that the stand-by telephone could be answered at any time.

6.4 Middle contact After about ten days the participant returned to the test centre, or in some cases was met at another prearranged point. At first the participant was asked informally how he or she had experienced the first time with the car, and whether anything unusual had turned up. Then the participant was given the middle questionnaire, asking about experiences with the car, attitudes and experiences about driving distracted or drowsy, as well as expecta-tions about a distraction and drowsiness warning system. The questionnaire can be found in Appendix 4. While the participant filled in the questionnaire, the experimenter plugged in the monitor, keyboard and mouse, enabled the warnings, exchanged the log hard disk and the video-log hard disk for new ones, and checked whether the equipment was in good working order.

Then the participant was given the new informed consent form, describing the warning system and the purpose of the study (see Appendix 3). The participant also received the manual of the study (Appendix 5). After signing the new form, the participant took a short trip with the experimenter in the back seat, who was monitoring the equipment. During suitable traffic conditions the participant was encouraged to try out the distraction warning system by provoking a warning. The drowsiness warnings were not demonstrated, but explained verbally. It was pointed out to the participant that he or she should avoid “playing around” with the system, because it was always dangerous to look away from the road for so long.

After agreeing on a date for returning the car, and after having cleared up any other business, the experimenter removed monitor, keyboard and mouse and the participant drove off with the car.

The experimenter archived the documents and assured again that the stand-by telephone was on and could be answered at any time.

6.5 Final contact When the participant came back in order to return the car, again an informal interview was conducted to catch spontaneous comments of the participant. The car, the system and the experimental design were subject of the interview.

Afterwards the participant was given the final questionnaire, mostly concerned with experiences with the distraction and drowsiness warning system, and with attitudes toward the system (see Appendix 4). The participant was then informed that it was planned to conduct a focus group in the end of the study, for which it was the goal to invite all participants in the study. The participant was asked whether it was all right to keep their name and address until the invitation was to be sent out in the end of the project, which was about nine months ahead for the first participant, but very soon for the last one.

When the participant had left the experimenter archived all documents, washed and refuelled the car, ensured that the safety equipment was complete and the car and data acquisition system in good order and refilled fluids like oil and windscreen washer

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fluid. The experimenter also disabled the warning system in order to prepare the car for the next participant, and exchanged the log-hard disks with empty disks.

6.6 Participant initiated contacts One telephone was on stand-by at all times for the participants to call in case that they experienced problems or had any other questions. Different members of the project team manned the telephone in order to guarantee continuous availability.

The number of phone contacts initiated by the participants were limited. They were mostly centred around changing meeting times for the middle and final contact. Some participants were worried about the high fuel consumption of the vehicle and asked for reimbursement for the extra costs, which was granted to them. One participant inquired whether friends of his were allowed to drive the car, which was declined. One report was made about screeching brakes, which were checked while the vehicle was in service before handed over to the next participant.

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7 Log data This chapter describes the data logged during the course of the study. Both question-naire data, continuous log data and video data were collected. Additionally the parti-cipants were interviewed when they returned the vehicle. The GPS log format was already described under chapter 4.5, and the video log was presented under chapter 4.6. The questionnaires can be found in Appendix 4.

The continuous text log was collected from six modules running in parallel and time synchronised, as well as from one GPS-receiver, which was not time synchronised with the other modules. The Warning Control Module steers the inhibition of warnings via rules described in Chapter 5.6. The SmartEye Raw Module converts the eye tracking data such that they can be read by other modules and saves the eye tracking data in a file. The Drowsy Server Module uses part of the data, mostly related to eye closure, from the SmartEye Raw Module for driver drowsiness classification. Those eye tracking data, together with variables concerning the driver state classification are saved. Also the IDP Module (Inattention Detection Programme) uses data from the SmartEye Raw Module, mostly gaze direction data as well as head direction and position data. The module saves those data together with output from the inattention detection programme. The In/Out Module handles the communication with external devices. It activates the seat vibration in case of a distraction warning, and it sends trigger information to the video logger. It also saves in/out data. Finally, the CAN Module reads data from the CAN bus and saves them in a dedicated file.

In Appendix 7 all variables saved in text files are listed for all six modules, together with a description of the triggers saved and some comments.

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8 Discussion of method This FOT-like study was the first of this size performed at VTI, however, considerable previous experience existed from field data collection, instrumented vehicles used for other projects, and driving simulator experiments. The main difference was the long-time unattended operation of the system, as well as the data collection and analysis part. Another difference was the use of the CAN bus of the vehicle to collect data.

The method in itself proved to be useful for a natural evaluation of driver distraction. A substantial number of distraction cases as determined by the distraction detection system in use were logged, indicating that the data sampling period was long enough in principle to obtain useful data material. Only few cases of drowsiness were observed, therefore it must be said that a study of this size is not enough for a systematic evalua-tion of a drowsiness warning system. Either the number of participants or the driving time per participant has to be increased. It might also be thinkable to select participants that are likely to drive drowsy, but whether this approach is feasible has to be deter-mined by the research question at hand.

The drivers stated that they did not feel disturbed or restrained by the log system. Several drivers commented that they only remembered that they were being filmed after having done something “embarrassing” like picking one’s nose. This, together with a rough evaluation of speed distributions and video reviews leads to the assumption that the drivers’ behaviour was very natural. Obviously driving a borrowed vehicle in-fluenced the participants, and more naturalism would have been attained, had the drivers’ own cars been instrumented. This was not feasible, however, for the present study.

The eye tracking quality remained stable over time after installation of an automatic recalibration based on the head model. The camera positioning was good; it occurred only rarely that the view of the driver’s face was obscured by the driver’s hand, for example. During 70–80% of the driving time eye tracking was available, and only for about 5–10% of the driving time tracking was lost completely. However, more exten-sive head turns often led to a loss of the gaze direction signal. In the present study the drivers were asked not to change the position of the driver’s seat too much, therefore no problems were encountered with the drivers’ disappearing out of view completely. Trips during daylight and in darkness produced comparable tracking results.

Anecdotal evidence, based on watching the videos recorded of the drivers’ head in com-bination with the output of the eye tracking signal, showed that the distraction warning system agreed in a majority of the observed cases with the analyst. It is more difficult to make a conclusive statement for the drowsiness warning system, both because only few drowsiness cases were recorded and because the drowsiness detection algorithm is not completely known to the authors of this report.

Many instances of natural distraction were recorded, which means that the purpose of the study was fulfilled, and the method worked as planned. However, it has to be said that in many instances of visual driver distraction eye tracking gets lost, due to the fact that the driver turns his head too far away from the camera to guarantee a good coverage of the face and eyes. One extra eye tracking camera on the middle console with a relatively low placement could probably improve tracking in those situations.

Obviously, the natural environment increases the external validity, but reduces controllability on the other hand. Between-subjects comparisons become difficult not only due to different driving patterns and environments between participants, but also

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due to lighting and weather conditions. Each participant used the car for about one month, meaning that there were participants that drove in winter, with very short daylight hours, mud on the road and cold temperatures, while others drove during the early summer with very long daylight hours and warm weather. Generally the long duration of the study can be seen as a disadvantage, because things change both in the environment, like the seasonal changes mentioned, and there is a larger chance that there will be changes in staff, too. In the present case one crucial group member changed employer, which did not lead to severe problems thanks to the flexibility of the involved partners, and because the project had already progressed quite far. However, it is crucial to be able to provide a backup quickly for important team members.

It became clear once again that it is of paramount importance to conduct thorough pilots, both for the equipment and for the procedure. Especially the equipment must be tested under a longer time period and under varying environmental conditions to assure its durability. If dedicated software is programmed, like in this case, extensive testing is necessary to remove all bugs before the main study is run. The procedure must be well learnt by all experimental leaders both to ensure a smooth interaction with the partici-pants and to guarantee that instructions are given in a similar way. This worked fine in the present study. It was tried to accommodate the participants as much as possible, which resulted in some participants being met and instructed at VTI, while other parti-cipants were met at their homes or other places convenient for the participants.

It had been planned to run eight participants, but in the end seven were run. Technical problems of the car itself and of the data acquisition system did not allow to fit eight participants into the planned schedule. As compared to studies which are more controlled, like simulator studies or test track studies, a greater range of difficulties was encountered here, which at times called for creative solutions. One major contributing factor that the goal of eight participants could almost be reached was the good coopera-tion in the core project group. None of the seven participants terminated the trial pre-maturely.

A detailed list of incidents that occurred and of “lessons learnt” is included here, both in order to be able to evaluate the results in the light of what actually happened, and in order to support researchers planning a similar study.

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9 Lessons learned In this chapter a number of considerations which might help improving the next study of that kind are mentioned, partly in an anecdotal fashion and partly as reflections in principle. Some of the comments are very specific for the present study, while others can be seen as more general.

9.1 Participants The selection of the participants has to be thorough, taking into consideration the main pre-requisites for a driver and the expected conditions at the time he or she will be driving. It is not always enough to rely on what potential participants report about themselves. Some participants are rather eager to participate in a study like this, which can lead to a tendency to answer certain questions in a manner that is expected to be desirable. It is, however, just as important to ask the correct questions. In the present study, for example, it could have been stressed more that it was paramount that only the actually recruited participant was allowed to drive the car. It might also be considered to try to control that the participants will drive in approximately the same environment both during baseline and during treatment. In the present study there were several occurrences when the baseline driving environment and mileage differed substantially from the treatment environment and mileage, rendering data analysis of certain aspects more difficult.

Instructions have to be very clear and exhaustive. Additionally, the participants must always be able to contact a person in charge of the study, this in case of problems with the vehicle. Some examples from the field study clarify how the factors named above can contribute in avoiding problems and data loss.

• A participant wore clothes that influence the gaze tracking equipment nega-tively. A headband or bandana covering part of the eyebrows jeopardizes tracking accuracy, especially if it is adorned with reflective material. A high collar where the chin is tucked in covers part of the face and degrades eye tracking. This should be made clear to participants, and they should be asked to avoid this, as functioning eye tracking is imperative for the system

• A participant shared the car with his partner. Changing profile for the eye tracking equipment was not possible automatically, thus all data for the partner were useless. Furthermore it was not recorded when the partner or the main subject were driving. This necessitated manual analysis of the video recordings in order to be able to use at least the data from the main driver. If other people than the main driver are allowed to drive the car, a device or recording function should allow clear determination of who is driving, without the need of manual analysis of the video data

• A participant drove very short trips, often shorter than 3 km. Here careful selec-tion of the participants should have excluded this participant, as data from short trips usually are less useful (computer start-up time creates significant data loss, low probability of drowsiness)

• One participant touched his nose very often and covered his face a lot with his hands in general. This led to degraded eye tracking

• Most participants noted that the field car consumed much more fuel than the car they are usually driving, creating a higher financial burden. Here a reimburse-

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ment was agreed on afterwards, in order to prevent the participants from quitting prematurely. However, it is preferable to include all information before the pilots start

• Very short or very long participants might not be able to be positioned well to be in full view of the cameras, this problems was not encountered for this study, however.

9.2 Vehicle The test car was a Saab 9-3 SportCombi Aero from 2007 with a 2.8 litre turbo engine and automatic transmission with six gears. The choice of the car should take environ-mental and economical aspects into consideration, as the participants also did when they commented about high fuel consumption of the car.

The preference should fall on a modern, safe car with very low fuel consumption. The trunk compartment should be large enough to fit all necessary equipment. The car needs a CAN-bus in order to ease data collection. Further considerations include which car types the target group usually uses. In general it is preferable to provide a car of similar quality. Lower quality might deter drivers from participating, while a much higher quality might lead drivers to exhibit untypical driving behaviour. There would also be risks for a slanted self-selection of the participants.

All insurance issues must be clarified to the drivers. Ethical approval processes must consider that the field car will be able to record position, video from inside the car and the outside, possibly sound, and driving data at all times. The driver needs to be aware that driving the car in certain locations will not be permitted (for example inside or in proximity of certain military areas).

All installed equipment must be as indiscernible as possible for the driver and from the outside. In fact, the vehicle should look just like a normal car. It has to be made sure that the installed extra equipment is crashworthy. If the spare wheel is replaced by log equipment, for example, a tyre repair kit should be provided.

A very critical point is humidity and temperature inside the car, and especially where the data acquisition system is located. Electronic equipment has a certain environmental operation range and can be damaged if the temperature is outside the range. Humidity can be removed with fans. Temperature can be between +5 and +40 degrees C. Thermo-statically controlled fans can extract heat from the car to the outside. Temperature below 5 degrees Celsius was a major problem, not only because it is precarious for hard disks, but also since certain equipment (such as the video recorder) would not operate below this range (note that hard disks with extended temperature range from -30 to +85 de-grees C are available, but they usually offer lower capacity, and would not have solved the problem with the video logger not starting). Thus a solution had to be found to raise the temperature in the logging compartment. This was necessary especially after the car had been parked outside in cold conditions, because it takes a long time for a cooled down trunk to be warmed up by the normal heating system of the car. Heating fans and heating pads are possible solutions, but is has to be considered how much power they consume. Ideally the car is already pre-heated when the drive starts; this is usually not possible as the battery could be drained. The chosen solution was to start heating (thermostatically controlled ceramic heating fan with power around 50 W) as soon as the car engine was started. This shortened the time it took for the car trunk to reach a temperature above 5 degrees Celsius. An additional battery was installed, which would

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charge together with the main car battery, and provide higher power and higher voltage stability than a single car battery.

An alternative solution is to isolate the car trunk against low-high temperature however, this poses a risk of being more vulnerable to over-temperature, generated from the electronic data collection equipment in the car trunk. Extended over-temperature should lead to an alarm and power-cut to all electronic equipment, in order to avoid a possible fire hazard.

The large amount of electronic equipment in the car disturbed the reception of the radio signal (FM mode), which led to a degradation of the sound quality. This annoyed several participants and led, as several participants reported, to an increased interaction with the radio, in search of a better channel.

9.2.1 Power module and power logic The hardware was mounted in the spare wheel compartment. No hardware (besides one box where a camera was hidden) were visible for the driver, when sitting in a normal driving position. At night the IR flashes were discernible as dark red disks behind the screens covering them. The forward scene camera, the camera filming the compartment, and two small GPS receivers were visible from different positions in the car.

An important requirement is that the hardware onboard should not draw so much power that the battery is discharged. Furthermore the voltage has to be very stable and within certain limits, here DC-DC converters and filters can be used. From the car battery the power was led through a control hardware in order to allow for the computer to shut down in a controlled way when the car was stopped and the ignition key removed, furthermore, functions for hard-resetting the computer were present. When the car engine starts (start-motor running) voltage usually drops and voltage spikes can arise, thus, electronic equipment should start first once the start motor is off. A power logic module controlled this feature. Voltage spikes arising from the start-motor of the car were filtered by the second battery and its protection circuits. All contacts and connectors were proofed for vibration resistance. For safety reasons no 110 or 230 Volt power was in the vehicle, all hardware was running on 12 Volt or lower voltage. The quality of the voltage, as well as the different voltages needed for the equipment, represented a problem in the field tests. Ideally the 12 V car voltage (which can range from 11 to 14 Volt) should be filtered, run through a DC-DC converter (with over-current and short circuit protection as well as output limit and input fusing) and then into the power module (power logic). Other voltages may be needed for the electronic equipment, here DC-DC converters should be used as well. The main DC-DC converter should have the highest power rating and the best protection, the other DC-DC converters can be connected to the output of the first converter. This gives higher protection and better voltage quality.

All DC-DC converters, cables, connectors, etc. must be sized to the expected maximal power rating. Hardware failure or short circuit in any component must not influence the normal car function. The charging module of the second battery must have a generous low-voltage cut off, which leaves enough power in the battery to be able to run the start motor of the car.

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9.2.2 Wiring It is important to ensure a well arranged wiring. All connectors and connections should be vibration-tolerant: Here problems were experienced with USB connectors, as they cannot be locked. Over time they were shaken loose, which resulted in either loose contacts or a complete disconnection. Firewire cannot be locked either, but seemed to be more vibration resistant. RJ45 (network) connectors are lockable and did not cause problems. Video and other analogue signals can be wired through RF/coaxial connec-tors (BNC), which are lockable. For the USB plugs either an industrial plug-assembly connector (which is vibration resistant) can be used, or the plugs should simply be blocked so that they cannot become loose. Resistance against vibrations must be considered for all connectors and plugs!

All wiring must be protected against short circuits. Here the basic solution is to use fuses. A comprehensive wiring scheme should be available in order to be able to track and solve technical problems.

9.2.3 Data acquisition hardware As mentioned, the data acquisition system was mounted in the spare wheel compart-ment of the car. Data was acquired from different sensors: vehicle data from the CAN bus, position data from GPS sensors, video data from cameras and gaze and eye blink data from the eye tracking system. A CAN bus interface collected relevant CAN data, whereas an AD-converter digitised other analogue data in the car. Besides the video recordings all data were stored via the computer (USB and Firewire connection) on an external hard disk. This allowed to replace the external hard disk quickly. The data was stored in simple ASCII files, this was seen as more robust and less resource consuming than opting for real time acquisition in a data base. The computer ran on Windows XP, algorithms and data collection routines were developed in C++.

If the recorded data is stored in ASCII-files or binary files, clear naming of the files is very important: each single file must be clearly identifiable by its name for source, date, time, type of data, start sampling and stop sampling time, etc. This was done by naming each file with the project ID, the vehicle ID, the log module ID, the driver ID, the date and the time of day. Different files, coming from different moduldes but from the same trip, differed only in the module ID. One file name could be: da-1-11-8050_071115_081952.log This file stems from the drowsiness and attention project, from vehicle 1 (the passenger car), from driver 11 and from the log module 8050, which is logging the output of the inattention detection algorithm. It was initiated on the 15th of November 2007 at 8:19:52 am. A more detailed description of the different modules can be found in the report on the results (Kircher, Kircher & Ahlström, 2009). This nomenclature worked well both for keeping track of the files and for analysis purposes.

9.2.4 Computer The part which created most problems in the field tests was the computer (AOPEN mini PC). Some reasons were:

• The capacity of the USB controller was not sufficient for all connected USB peripherals, thus some peripherals had to be run at USB 1.0 instead of 2.0

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• Very limited choice of expansion cards, as the only expansion possibility was to use mini-PCI cards

• Limited number of available connections (USB, video out …)

• Operative system: It is important to disable all automatic update functions. Linux is the first choice as operative system, because it allows a better control. In Windows many automatic functions are present that cannot be turned off, or that only appear after a while, disturbing the data acquisition system. We had to use Windows XP Pro, since not all required software was available for Linux

• After a while Windows notifies the user that there are certain icons on the desktop that are not often used. This notification covered part of the information on the screen that was recorded via the video logger. In the beginning of the study the start task menu bar moved up and covered the lowest part of the recorded screen when the notification popped up, but that was removed by sending the task menu bar to the background. It is paramount to turn off as many of the automatic features of the operative system as possible.

While the sixth participant was driving, that is, after about a year of the computer having been installed in the car, the stability of the computer decreased significantly. It could not be ascertained whether this was due to voltage problems, or a result of many unplanned hard reboots, which in turn were most likely a result of voltage problems. The problem could not be solved before the last participant received the car, and resulted in a substantial and inacceptable data loss of up to 30% of the distance driven for the last participant. It is suggested that an identical, second backup computer is available in case the main computer has a major problem. The backup computer should have a mirrored hard drive from the main computer. This allows replacing the computer, reconnect all cabling, and continue the experiment without considerable time delay.

9.2.5 Monitor, keyboard, mouse inside the car A standard computer keyboard and mouse were used. The monitor was a 12 V operated TFT 17” screen, with an option to connect VGA and FBAS video. This allowed to connect the computer and to control the camera outputs directly. Computer, keyboard and mouse were only installed when the experimenter met the participant, not while a participant was driving during the baseline and the experimental phase. Here a better option would have been to use a wireless keyboard with integrated mouse, because the way it was, cables had to be led to the front seat of the car while setting up the system or creating profiles.

In the case of this study the cable that led to the front passenger seat got caught under the sledge of the seat, was damaged and had to be replaced. Apart from causing incon-venience to the experimenters, there is also a potential of causing problems for the participant.

9.2.6 Mobile network connection The idea with the mobile network connection via 3G (or GSM) was to be able to connect to the computer of the car, check equipment status, receive possible warnings and error messages, and download data. Furthermore, the car position and the driver can

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be seen in real time, because it is possible to log into the computer of the car and connect to the web server of the video recorder. In a test environment this was success-ful, but the system could not be used in the car because of software incompatibility issues.

Using a mobile 3G network connection usually means obtaining a dynamic IP-address, here DNS redirecting services can be used to be able to use a static IP-address instead.

Generally it is very recommendable to employ some sort of remote monitoring when a longer study without experimenter contact and intervention is planned to ensure the quality of the data and the functioning of the equipment. If a solution like the one intended here is not feasible, a report via SMS after every trip or day would be another possibility.

9.2.7 Smart Eye Pro Initially Smart Eye Pro 4.0 was used for eye tracking. During piloting it was observed that the tracking degraded significantly over time. This went hand in hand with a quickly degrading camera calibration. This was traced back to slight position shifts of the cameras, which were a result of an expansion of the front console of the vehicle when the temperature rose. Overnight, when the car cooled down, normal performance could be observed again.

An update was provided for the Smart Eye Pro system which recalibrated the cameras based on the head model every hour in order to compensate for changing temperatures. This worked very well, and the eye tracking results were generally good.

During piloting drivers wearing glasses were run in order to check the functioning of the eye tracker under these circumstances. It turned out that the tracking quality varied substantially between drivers. Some glasses, especially when they were not too strong, not reflecting and did not have a heavy frame, resulted in acceptable tracking results, while others led to substantially degraded tracking. In the study only participants without glasses were allowed.

Similar problems are possible, but were not tested systematically, for drivers with a beard or with heavy make-up. All drivers in the present study had light skin.

The version used in the present study did not allow automatic profile generation. The profile had to be generated manually via a cumbersome process that took at least 20 minutes, had to be saved in the correct location on the hard disk, had to be given the correct name, and the correct driver ID linked to this profile file had to be entered into the computer. This process was time consuming and error prone. Furthermore, it required that the experimenters be trained in profile generation. Additionally and most important, it meant that only one driver at a time could have a working profile; for other drivers the eye tracking system did not work with a wrong profile. These are big disadvantages, and it is highly recommended to opt for an eye tracker with automatic profile generation, if available.

For profile generation it was initially planned to film the participant in the car, but to generate the profile on another external computer with a better screen and a more convenient work environment. It turned out, however, that the profiles generated on the other computer in the same software version produced very large tracking errors in the car, for unknown reasons. Therefore the profile was generated in the car with the

58 VTI rapport 638A

drawbacks of a cramped work environment and a small computer screen of moderate quality. This may have reduced the quality of the profiles.

9.2.8 Mobile hard disk The mobile hard disk consisted of an enclosure with a Fire wire interface and a 2.5 inch hard disk. Two mobile hard disks were used by swapping them in order to smooth and speed up data collection.

The selected hard disk model was appropriate in terms of ruggedness, memory space and connections. The main requirement is reliability, which dictates choosing hard disks with high operating shock specifications. The chosen model (Hitachi Travelstar 4K120 HTS421212H9AT00) has 300 G operating shock and 1000 G non-operating shock, as well as 600 000 load/unload cycles specifications. Temperature range is 5 to55 degrees Celsius (operation) and -40 to +65 degrees Celsius (non-operating). There are hard disks which have even higher specifications (see the Endurastar series of Hitachi), but these have much lower capacity (max 50 GB for 2.5 inch drives). The main risk in the setting encountered in the field car was actually the minimal temperature. Since the car trunk was not temperature controlled for low temperature, the temperature could be lower than 5 degrees Celsius. Over night the temperature inside the car adapted completely to the outside temperature, which lay between -15°C and -10°C at several occasions. Reheating was very slow in the trunk compartment. This created a risk for the hard disk and the data, because of the shrinking distance between hard disk heads.

Choosing a 2.5 inch instead of 3.5 inch model came from the better shock tolerance of the smaller models. In order to increase reliability a double hard disk data collection system could be used, either with Raid 1 configuration, or simply saving the data to two independent hard disks.

The hard disk enclosure was fixed to a wooden board; here it is advisable to place a damping pad between enclosure and surface.

The 2.5” enclosure was a standard model with Firewire 800, USB 2.0 and DC input connection. External power connection was not needed, as both Firewire 800 and USB carry power to the device. Note that both the Firewire 800 connection, and the power connection could become loose from the vibrations, thus precautions have to be taken. If the connection to the log harddisk fails, no data at all will be collected any more.

The same discussion as for the mobile hard disk is valid for the computer’s internal hard disk and the hard disk of the video recorder. In the present case the same type of 2.5 inch hard disks were used for computer and mobile hard disk. No problems with the log harddisks were encountered during the course of the study.

9.2.9 GPS sensors No problems were encountered with the GPS sensors, and the simple models proved to be adequate for the task. The update rate of 1 Hz was sufficient for position tracking. Again, the main note here is the USB connector of the sensors, which can become loose due to vibrations.

Since there were two applications using GPS position in the field tests, two sensors were used. This solution was simple, cheap, and redundant, and was preferred towards sharing the USB COM port between both applications.

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The GPS receivers were placed close to the window on the left hand side in the rear part of the car. It is important to know that the received NMEA data is not usable before the GPS receivers have satellite fix, and the recording software should account for this. Computer clock can be adjusted and synchronised once the receivers have satellite fix.

9.2.10 Digital mobile video recorder and cameras The digital video recorder stored four video inputs: computer screen, real time map (GPS position), vehicle front view, and driver.


− Digital hard disk drive recorder

− Long time recording (over 20 days)

− Full stand alone operation

− Mobile hard drive recorder, rugged construction for in-vehicle use

− Programmable settings for recording

− Possible to export videos in common format (for example avi or mpg)

− Local support.

The selected model was a Heitel CamMobile 4 (with 4 camera inputs, no sound card and swappable hard disk). Here the lesson learnt is that ease of use of the recorded data is very important. Some recorders use a proprietary format not only for the video data, bus as well for storing the data on the internal hard disk.

The space needed for recordings on the hard drive is dependent on:

− frame rate (frames per second)

− bit rate (image recording quality)

− resolution

− compression technology

− number of cameras

− audio recording (yes or no)

− color or b/w image

− content of image

− duration of recording.

In the present field test the 120 GB hard disk was just sufficient for recording typical driving during the baseline respectively treatment phase (around 2-3 weeks). It happened, though, that the storage capacity for one of the cameras was exceeded slightly by the driver with the highest mileage. If possible a hard disk with a higher storage capacity should be selected, because an increased frame rate would improve the viewing quality. (At the time of writing the maximal capacity of 2.5 inch hard disks is 500 GB). A second hard disk was available in order to allow for fast replacement when needed. Usually the hard disk was replaced during the shift from baseline to treatment phase. A USB enclosure allowed to connect the hard disks of the video recorder to a computer.

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All cameras (especially the cameras for the eye tracking equipment) must be mounted in a way that they cannot be moved accidentally, do not represent a safety threat for driver and passengers, are unobtrusive, and fastened such that vibrations do not affect position or image quality. The scene cameras must be able to record at very low light levels. Here there are two possibilities: IR-capable cameras with IR-LEDs, and high-sensitivity cameras able to operate at light levels down to 0.02 Lux. IR-LEDs positioned behind the driver can disturb the eye tracking cameras placed in front of the driver. In the field test car a problem with IR-cameras was experienced: When the ambient light level fell below a certain level the camera would automatically switch to IR-operation, but this is relais-controlled, and the switching was audible for the driver.

IR-cameras are usually much smaller than high-sensitivity cameras. Black and white cameras are usually sufficient, additionally the recorded data take much less space than colour video. Cameras should have automatic gain control, automatic shutter speed and back light compensation.

It is important to decide if the video recording is done via external video recorders (as it was the case in the field tests) or via the computer (video grabber card and storage on the hard disk of the computer). Both solutions have pros and cons; it should be consi-dered that video data occupies much hard disk space, and the compression is processor intensive.

Recorded video should contain information about vehicle location (moving map), driver (front view or side view), road (camera facing forward), etc., depending on the research question. Critical situations (for example warnings given by the system or extreme accelerations) should be marked in the video to make it possible to jump to such events directly. Another feature which was used in the field test was different video recording quality (in terms of resolution and compression) for different camera views. Higher frame rate when critical events occur are an option, but were not used in the present study.

9.2.11 Distraction algorithm and warning Before the study was conducted it was hard to guess how many distraction warnings would occur with the algorithm used. Even though the pilot phase helped getting a feeling for that, much emphasis of the piloting was put on getting the data acquisition system to work correctly, which meant that the algorithm in itself was neglected more than it should have been. More extended piloting with naïve participants would have helped to adjust the algorithm in order to reduce the frequency of the warnings.

Generally the distraction warning functionality worked well throughout the study and was not experienced as disturbing by the drivers. One driver noted that she could feel the vibration pads in the seat also when they were inactive, but did not report that as inconvenient. One driver complained about too many distraction warnings, and often unmotivated warnings.

For further improvement of the algorithm, and generally for driver distraction research, it would be useful to have and log a generally accepted ground truth measure for driver distraction. If such a ground truth, a criterion that researchers agree upon to be a sure indicator of driver distraction, were available, it could be determined without doubt whether a system actually warns for driver distraction or something else. It would also allow a truthful comparison of several algorithms, instead of having to rely on

VTI rapport 638A 61

indicators that are assumed to be representative of distraction, without necessarily being sure.

9.2.12 Drowsiness warning algorithm Several participants reported that they did not get many drowsiness warnings at all, and those they received were not experienced as very accurate. This is, however, the subjective opinion of the drivers, and for confirmation or rejection purposes of the appropriateness of the warning it would have been useful to have at least one other means of assessing driver drowsiness. In an FOT-like setting this is not very easy, however, as the driver cannot be asked to rate his drowsiness in five-minute intervals. It is out of the question to use obtrusive equipment like electrodes. The only rather rough impairment indicator that could be used are vehicle based measures.

9.2.13 Drowsiness warning The drowsiness warning consisted of a display and a speaker. No problems were encountered with the display besides an unwanted welcome message shown every time the computer booted. The speaker was a small active PC speaker placed behind the rear seat. The sound quality was barely acceptable. The power cable of the speaker was detached coincidentally at times when the participant used the luggage screen cover of the trunk. Selecting a proper speaker volume was problematic. In order to prevent that the volume of the car audio system could mask the warning message the radio was muted when the spoken warning was given. It is suggested to use the car speakers for the audible warnings in the future.

9.2.14 Display For the development of the distraction detection algorithm and for piloting it was very important to have a display which showed on-line the current distraction and drowsiness status, where the driver was looking, and several other variables such as quality of the tracking, the current speed, etc. This display was also used while the experimenter took the participant on a test-ride in order to check whether the eye-tracking profile worked, and whether all other equipment was functioning. It was disconnected before the driver set off with the vehicle alone.

In hindsight it would have been advantageous to have more space for the face view of the participant, and to have a higher update frequency of the face view, and also of the over-the-shoulder view, in order to perform a manual validity analysis of the gaze tracker. It is considered to be very promising to be able to compare the performance of the automatic eye tracker with several human data reductionists. However, hard disk space limited the update frequency in this case.

9.2.15 Data logging A large amount of data are typically logged during field tests. If a database solution is implemented from the beginning, or if data is first stored as single ASCII or more space saving binary format files and then added to a database should be decided from the beginning. In our case we opted for a simple solution logging data to files in ASCII format. This had the disadvantage that the data took more space compared to binary

62 VTI rapport 638A

format, and were not organised, but on the other hand they were very easy to visualise (ASCII against binary format).

A database solution for data collection is probably the best solution; typical data collec-ted in field tests is usually stored in relational databases, MySQL and PostGRESQL are powerful open source database solutions which would be suitable here. One important factor is that error detection can be implemented in real time on the collected data (for example to discover a sensor malfunction). Secondly, a database offers a much higher level of organisation of the collected data, which is important for large amounts of data. A high level of SQL standard compliance is important for the database software, as well as speed and stability.

Another possibility is to enter the data in a database after the data is being collected in binary format.

As mentioned early it is important to ensure that the data are safely stored, comprising both redundancy and error tolerance. Redundancy can be obtained by for example storing the data on two hard disks at the same time (RAID 1 solution) or on the internal computer hard disk as well as on an external hard disk. Error tolerance is present when a sensor loss does not lead to losing all data.

As in any scientific research the hypotheses should control the data to be collected. Just collecting all possible data only leads to high memory requirements.

Synchronisation of the different data recorded is imperative: all video data, vehicle data, GPS data, etc. must be synchronised. The internal clock of the computer (which itself is adjusted via GPS) can be used for this purpose. If data have different sampling frequen-cies (which is normally the case) the sampling times should be multipliers, such that each sample of the data with the lowest sampling frequency is synchronised with the corresponding sample of data sampled at higher frequency.

Sampling frequency is a compromise between resolution and memory space. Some signals, such as eye gaze data, need high sampling speed, ideally at least 60 Hz, GPS data have usually 1 Hz, and data such as temperature will require only one sample per minute for example.

9.3 Design and procedure The study design was a simple baseline-(A)-treatment-(B)-design, which worked well, but obviously carried the usual risks for confounding which come with this type of setting. Due to the limited time frame per participant and to avoid chunking this time into smaller periods it was decided not to use an ABA- or even ABAB-design. As the participants should not be informed about the distraction warning system during baseline driving, using a BA-design for half of the participants was not possible.

It proved to be very important to be flexible and to meet the participants’ needs. This kept their attitude positive towards the research setting and some inconveniences connected to it, like having to reserve time to meet the experimenter in between, not wearing sunglasses, coping with the low quality of the radio, and so on.

The participants were told that they could always call a certain telephone number if they needed any assistance. This telephone would be available as much as possible. As the number of participants was rather low and not too many calls were expected, no formal stand-by schedule for the telephone was set up, rather, the experimental leaders took turns in taking responsibility for answering the telephone. Even though this worked well

VTI rapport 638A 63

in this case, it is recommended to have a schedule for who is responsible for the telephone, and to provide some reimbursement for those on stand-by.

Several calls were made for different reasons, ranging from rescheduling the meeting times over asking whether one’s friends were allowed to test-drive the car, to questions what to do when the battery in the key failed. Altogether about 20 calls were made by the seven participants.

9.4 Data analysis In the case of the present study a programming error were detected first after the first participant had done baseline driving, and it could only be corrected after the first participant had finished driving. In order to prevent something like this from happening it is paramount to run a pilot that is long enough to be able to detect all crucial errors, and to thoroughly analyse the pilot data. This means that there should be ample time between the pilot and the main study, which allows for adjustments and corrections.

Further comments regarding data analysis are made in the third report of the series, in which the results are presented.

64 VTI rapport 638A

10 Conclusions As so many times before, the major methodological insight was the importance of conducting a thorough pilot study. Such a pilot should be done full time, and enough time should be reserved for making final adjustments before the regular participants are run. This, however, is no guarantee that no further problems will occur during the course of the study. Then, creativity, engagement and the notion that it is of paramount importance to ensure that the participants experience as little inconvenience as possible are the key to success.

Even though a number of drawbacks related to control and, thus, complicating data ana-lysis are inherent to the study design of an FOT, this method proved to be very pro-mising for a naturalistic long-term assessment of driver support systems. It was found that the use of remote eye trackers in a field setting like the one described here is fully feasible, and it is very likely that the technological development will simplify the employment of remote eye trackers further.

VTI rapport 638A 65

References Almén, L. (2003). Reducing the effects of driver distraction: A comparison of distrac-tion alerts on driver attention. Linköpings universitet, Linköping.

Donmez, B., Ng Boyle, L. & Lee, J. D. (2006). The impact of distraction mitigation strategies on driving performance. Human Factors, 48(4), 785–840.

Donmez, B., Ng Boyle, L. & Lee, J. D. (2007). Safety implications of providing real-time feedback to distracted drivers. Accident Analysis & Prevention, 39(3), 581–590.

Donmez, B., Ng Boyle, L., Lee, J. D. & McGehee, D. V. (2006). Drivers' attitudes toward imperfect distraction mitigation strategies. Transportation Research Part F, 9, 387–398.

Ervin, R., Sayer, J. R., LeBlanc, D., Bogard, S. et al. (2005). Automotive collision avoidance field operational test. Methodology and results. Volume 1: Technical Report (Technical Report No. UMTRI-2005-7-1; US DOT HS 809 900). Ann Arbor, MI, USA: University of Michigan Transportation Research Institute.

Karlsson, R. (2005). Evaluating driver distraction countermeasures (VTI notat No. 28A-2005). Linköping: VTI (Swedish National Road and Transport Research Institute).

Kircher, K. (2007). Driver distraction: A review of the literature (VTI rapport No. 594A). Linköping, Sweden: VTI (Swedish National Road and Transport Research Institute).

Kircher, K., Ahlstrom, C. & Kircher, A. (2009, submitted). The relationship between glance direction and eye tracking quality based on data from a long-term field study. Paper presented at the ITS World Congress 2009, Stockholm.

Kircher, K., Kircher, A. & Ahlström, C. (2009). Results of a field study on a driver distraction warning system (VTI rapport No. 639A). Linköping: VTI (Swedish National Road and Transport Research Institute).

Klauer, S. G., Dingus, T. A., Neale, V. L., Sudweeks, J. & Ramsey, D. (2006). The impact of driver inattention on near-crash/crash risk: An analysis using the 100-car naturalistic driving study data (Technical Report No. DOT HS 810 594). Washington DC: NHTSA.

Kovordányi, R., Kolleger, P., Claezon, F. & Granlund, R. (2009, in press). IVSS Driver attention – dealing with drowsiness and distraction. Field operational test of two warning systems using an instrumented Scania truck (No. tbd). Linköping: IDA, Linköping University.

LeBlanc, D., Sayer, J. R., Winkler, C., et al. (2006). Road departure crash warning system field operational test: Methodology and results. Volume I: Technical Report (Technical Report No. UMTRI-2006-9-1). Ann Arbor, MI, USA: The University of Michigan Transportation Research Institute (UMTRI).

Lee, J. D., McGehee, D. V., Brown, T. L. & Reyes, M. L. (2002). Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator. Human Factors, 44(2), 314–334.

Stutts, J. C., Feaganes, J., Rodgman, E. A., et al. (2003). Distractions in everyday driving (Report prepared for AAA Foundation for Traffic Safety). Washington, DC.

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Stutts, J. C., Reinfurt, D. W., Staplin, L. & Rodgman, E. A. (2001). The role of driver distraction in traffic crashes (Report prepared for AAA Foundation for Traffic Safety). Washington, DC.

Tijerina, L., Parmer, E. B. & Goodman, M. J. (1999). Individual differences and in-vehicle distraction while driving: A test track study and psychometric evaluation. Paper presented at the 5th ITS World Congress, Seoul, Korea.

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Wikman, A.-S., Nieminen, T. & Summala, H. (1998). Driving experience and time-sharing during in-car tasks on roads of different width. Ergonomics, 41(3), 358–372.

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INFORMATION OM FÖRSÖKET

Vi söker försökspersoner som vill delta i ett långtidsförsök där vi vill studera vanligt körbeteende. Försökspersonen får låna en bil under en månad och ska använda den som tjänstebil och privatbil. En närmare beskrivning finns nedan.

BILEN Modell: 9-3 SportCombi Aero, årsmodell 2007 Färg: blå Motor: 2.8T; V6, 250 hästkrafter Växellåda: automatlåda med 6 växlar Bensin: strax över litern per mil vid blandad körning

FÖRSÄKRING Bilen har trafikförsäkring, vilken täcker personskador och dyl. som med vilken bil som helst. Vid haveri kontaktas försöksledaren och Saab Assistance som sedan tar hand om bilen (bärgning eller starthjälp). Föraren ansvarar själv för eventuella trafiköverträdel-ser och parkeringsböter. Detta förpliktar föraren sig till genom att skriva på ett formulär.

VI SÖKER PERSONER MED FÖLJANDE EGENSKAPER Du ska ha haft körkort i minst 7 år. Du ska köra minst 2000 mil per år. Eftersom vi kommer att registrera blickriktning letar vi efter personer som inte har glasögon, skägg eller använder mycket smink. Detta kan störa mätutrustningen, så att vi får sämre data.

VTI POST/MAIL SE-581 95 LINKÖPING BESÖK/VISIT OLAUS MAGNUS VÄG 35 TEL +46 (0)13 20 40 00 FAX +46 (0)13 14 14 36 WEB www.vti.se FAKTURAADRESS/INVOICE ADDRESS STATENS VÄG- OCH TRANSPORTFORSKNINGSINSTITUT, 581 95 LINKÖPING

STYRELSENS SÄTE LINKÖPING ORG NR 202100-0704

Appendix 1Page 1 av 2

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SÅ HÄR GÅR DET TILL

Du kommer till VTI i Linköping för att hämta bilen. Detta tar ca 2-3 timmar, eftersom du ska få detaljerad information angående försöket, och vi måste kalibrera blickmätsystemet. Dessutom får du några enkäter att fylla i, och vi ber dig skriva på att vi får samla in data medan du kör. Dessa data kommer vi självklart inte att lämna ut till någon utomstående. Vi ska också köra en kort testrunda tillsammans för att ge dig en chans att ställa frågor som kan komma upp under körningen och för att kolla att mätutrustingen fungerar som den ska. När allt detta är avklarat få du ta med dig bilen, och sedan kan du använda den som din egen och som tjänstebil under en månad. Vi ber dig bara att komma till VTI en gång under lånetiden. Vid denna tidpunkt vill vi gärna omkalibrera blickmätsystemet, och vi kommer att be dig fylla i ytterligare en enkät. Besöket hos VTI vid detta tillfälle kommer att ta omkring 2 timmar. När du lämnar bilen efter lånetiden kommer vi också att be dig fylla i enkäter, och att svara på några frågor.

VAD SOM FÖRVÄNTAS AV DIG Vi ber dig ta hand om bilen som om den vore din egen. När du får bilen är den fulltankad och alla vätskor är påfyllda. Du förväntas ta över kostnaderna för bensin och spolarvätska etc., om det behövs. Vi ber dig att du inte låter någon annan köra bilen om det inte är nödfall.

KONTAKT Om du har ytterligare frågor hör gärna av dig till: Katja Kircher VTI 581 95 Linköping 013-20 4118 [email protected]

Birgitta Thorslund VTI 581 95 Linköping 013-20 4158 [email protected]




VTI rapport 638A

Lån av fordon

Dnr: 2006/0226-26

Tillfälligt lån av fordon Fabrikat: Saab Aero 93

Reg.nr.: ANA 964

Mätarställning:

Lånedag:

Låntagare:

Adress:

Telefon:

Körkort nr.:

Körkort kontrollerat:

Returdatum:

Villkor

Låntagaren svarar för att fordonet framföres av person med giltigt körkort och med beaktande av gällande lagar och förordningar. Enbart låntagaren har tillstånd att köra fordonet. Eventuella felparkeringsavgifter, böter m m, ävensom självrisker och kostnader för reparation av skador, som uppstår under lånetiden och som inte ersätts genom försäkring skall betalas av låntagaren. Vid eventuell skada på eller stöld av det utlånade fordonet skall långivaren underrättas omgående. Låntagaren får inte skriftligen eller muntligen påta sig något ansvar vs. 3:e man för inträffad skada förrän långivaren lämnat sitt medgivande därtill. Ersättning för eventuell reparation eller service, som ej beordrats av långivaren, godkännes således inte. Skadeanmälan skall ifyllas omgående, undertecknas och inlämnas till långivaren som handlägger skadan. Om inget annat är avtalat, skall låntagaren svara för de driftkostnader som uppkommer under lånetiden. Långivaren reserverar sig rätten att efter underrättelse till låntagare, säga upp lånekontraktet med omedelbar verkan. Långivaren reserverar sig rätten att debitera låntagaren för kostnader hänförda till krav gällande det utlånade fordonet. Undertecknad godkänner ovanstående villkor och bekräftar härmed mottagandet av nämnda fordon. Låntagaren svarar för eventuella skatter/avgifter som är hänförliga till låntagarens disposition av fordonet. Linköping, , låntagare: utlämnad av:




VTI rapport 638A

VTI rapport 638A

Bakgrund och syfte

Tack för att du är intresserad av att delta i vår studie. Som du kanske vet inträffar varje år flera hundra dödsolyckor och många fler med svårt skadade bilister på Sveriges vägar. För att kunna förbättra trafiksäkerheten är det inte bara viktigt att studera olyckorna, men också vanligt körbeteende. Syftet med den här studien är att samla in information om bilkörning under så naturliga förhållanden som möjligt. Förfrågan om deltagande

Eftersom du visade intresse för studien och uppfyller alla krav som vi har på försökspersonerna (B-körkort i minst 7 år, mellan 25 och 60 år, årlig körsträcka över 2000 mil, äger egen bil) tillfrågas du om du vill delta i denna studie som beskrivs nedan. För att bekräfta ditt samtycke ber vi dig sedan att skriva på att du är beredd att vara med under de beskrivna förutsättningarna. Hur går studien till?

Först skulle vi vilja ta en kort film på dig medan du sitter i bilen, så att vi kan fastställa din sittposition. Baserat på den kan vi sedan mäta dina ögonrörelser medan du kör. Du kommer att fylla i några frågeformulär som handlar mest om din uppfattning om några aspekter av bilkörningen. Vi ber dig också skriva på ett formulär angående dina rättigheter och plikter i samband med lånet av försöksbilen. Sedan kör du en runda på ca. 15 till 30 minuter tillsammans med en försöksledare som visar dig vägen och kontrollerar att mätutrustningen fungerar. Du kan alltid ställa frågor om du undrar över någonting. Sedan får du, om du samtycker, en liten apparat som ser ut som ett armbandsur. Den mäter rörelser och ger på så sätt information om när du sover och när du är vaken. Du ska ha den på handleden så mycket som möjligt under hela försökstiden. Ta av den enbart när du duschar eller badar. Därefter tar du bilen med dig hem och vi ber dig att använda den precis som din egen bil. Bilen fungerar precis som en vanlig personbil. Vi ber dig komma tillbaka hit med bilen den _________________ för nya instruktioner. Vad är riskerna?

Riskerna är desamma som uppstår när man kör en bil som man inte är van vid i vanlig trafik. Försöksledarna kommer t. ex. att kunna rekonstruera körda rutter och hastigheter, men inga brott mot trafikregler som hittas i datamaterialet kommer att polisanmälas (mer detaljerad information se ”hantering av data och sekretess”). Finns det några fördelar?

Genom att kunna använda en lånad bil istället för den egna reduceras värde-minskningen på den egna bilen. På längre sikt är syftet med projektet att öka trafiksäkerheten.

1


VTI rapport 638A

Hantering av data och sekretess.

Insamlade rådata kan spåras till dig, eftersom vi loggar sträckan och filmar dig. Vi publicerar dock ingenting som kan spåras till dig om du inte uttryckligen ger oss tillstånd till det. All rådata kommer att lagras i en databas hos VTI. De andra företag och institut som deltar i projektet har tillgång till databasen. De som kommer att ha tillgång till rådata är forskare som deltar i projektet, men ingen utanför. Dina svar och dina resultat kommer att behandlas så att inte obehöriga kan ta del av dem. Publicering kommer att ske i form av vetenskapliga artiklar, konferensbidrag och rapporter. Data kommer att sammanställas på ett sätt som gör att det inte går att spåra till dig. Hur får jag information om studiens resultat?

I den utsträckning som data kommer att analyseras för individer kan du kontakta VTI för att få information om dina personliga resultat. Referenser till publicerade artiklar och dyligt kommer att finnas på VTIs hemsida. Försäkring, ersättning

Så länge du vistas på VTI är du försäkrad genom en försäkring som täcker alla VTIs försökspersoner. Själva bilen har trafikförsäkringsskydd. Reparationer sköts av SAAB. Ingen ersättning förutom lånet av bilen utgår. Frivillighet

Ditt deltagande i detta forskningsprojekt är frivilligt, och du kan när som helst utan särskild förklaring avbryta försöket. I det fallet ber vi dig att kontakta oss så att vi kan arrangera ett lämpligt överlämnande av fordonet. Ansvariga

Huvudansvarig för genomförandet av studien är: Katja Kircher VTI S-581 95 Linköping besöksadress: Olaus-Magnus-väg 35 Tel.: 013-20 4118 (växel: 013-20 4000) e-post: [email protected] Andra projektdeltagare är Saab, Scania, SmartEye, Siemens VDO och Linköpings Universitet (IDA)

2


VTI rapport 638A

mailto:[email protected]

Jag har informerats om studiens förlopp, jag har fått tillfälle att ställa frågor och frågorna besvarades tillfredställande. Jag vet att jag kan avbryta studien när som helst utan att ge någon särskild förklaring. Jag måste då genast överlämna bilen till försöksledarna. Jag tillåter att data som inte kan spåras till mig (t. ex. en hastighetsprofil eller genomsnittsvärden över alla försökspersoner) får publiceras i vetenskapliga artiklar och rapporter, presentationer på konferens, seminarier eller liknande och populärvetenskapliga artiklar. När det gäller publicering av data som kan spåras till mig blir jag tillfrågad separat. Datum och underskrift

3


VTI rapport 638A

Hittills har du hjälpt oss förstå förarbeteendet under vanlig bilkörning – tack för ditt deltagande! Som du kanske vet är distraktion och trötthet bidragande faktorer i många olyckor. Därför vill vi utvärdera ett varningssystem som talar om för föraren när man har tittat bort från vägen för länge, eller när man är för trött för att köra på ett säkert sätt. Ett sådant system finns i bilen som du kör just nu. Systemet slås på i samband med ditt besök här på VTI, och du kommer att kunna känna på systemet medan du kör en testrunda med en försöksledare. Närmare information angående systemets funktion hittar du i manualen som du får av försöksledaren. Vi ber dig minimera tiden där du utforskar och testar systemet; försök att inte ”leka” med systemet längre än en dag. Tänk alltid på att det är farligt att titta bort från vägen under en längre tid, även när du medvetet provocerar systemet! Du är den enda som har tillstånd att köra denna bil. Tänk på att systemet är inställt så att det fungerar just på dig. Om någon annan skulle köra bilen (t. ex. i en nödsituation) så kan det hända att denna person får många felvarningar, eftersom systemet då inte kan fungera på rätt sätt. Om du upplever några som helst problem med bilen eller systemet ber vi dig att informera oss så fort som möjligt. Telefonnumret som du alltid kan ringa till finns i bilen (försöksledaren visar dig). Om du får motorstopp eller andra problem som gör att bilen inte längre är körbar var god och ta kontakt med oss. Vi ska se till att du får hjälp så fort som möjligt.

1


VTI rapport 638A

Jag har informerats om studiens förlopp, jag har fått tillfälle att ställa frågor och frågorna besvarades tillfredställande. Jag vet att jag kan avbryta studien när som helst utan att ge någon särskild förklaring. Jag måste då genast överlämna bilen till försöksledarna. Jag tillåter att data som inte kan spåras till mig (t. ex. en hastighetsprofil eller genomsnittsvärden över alla försökspersoner) får publiceras i vetenskapliga artiklar och rapporter, presentationer på konferens, seminarier eller liknande och populärvetenskapliga artiklar. När det gäller publicering av data som kan spåras till mig blir jag tillfrågad separat. Datum och underskrift

2


VTI rapport 638A

VTI rapport 638A

Fp (P): __________ Datum: __________________

Enkät före körningen

1. Vilket år tog du körkort för personbil? _______

2. Hur många mil per år kör du uppskattningsvis personbil? _____________

3. Hur många mil tror du har du hittills kört personbil (i hela ditt liv)? _____________

4. Hur ofta brukar du köra på samma sträcka (t. ex. pendlar du samma väg till och från jobbet)?

mycket sällan mycket ofta

5. Hur ofta kör du sträckor som är …?

aldrig sällan ibland ofta mycket ofta

a. < 2 km

b. 2-5 km

c. 5-20 km

d. 20-100 km

e. > 100 km

6. Hur ofta kör du …? aldrig sällan ibland ofta mycket

ofta a. mellan kl. 6.00 och 21.00

b. mellan kl. 21.00 och 24.00

c. mellan kl. 0.00 och 6.00

7. Hur ofta kör du …? aldrig sällan ibland ofta mycket

ofta a. i tätort

b. på landsväg

c. på motorväg

8. Hur ofta har du …? aldrig sällan ibland ofta mycket

ofta a. inga passagerare

b. vuxna passagerare (16 år och äldre)

c. barn mellan 0 och 5 år i bilen

d. barn mellan 6 och 16 år i bilen

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Bilaga 4Page 1 av 21

VTI rapport 638A

9. Vilka informations- och säkerhetssystem har du i din privatbil eller tjänstebil?

privatbil tjänstebil a. navigationssystem b. avåkningsvarning c. night vision d. adaptiv farthållare (anpassar hastigheten till bilen framför) e. kollisionsvarning f. parkeringsassistens g. backvarning h. annat: ____________________________ i. annat: ____________________________

10. Tycker du om att köra bil?

ja, mycket nej, inte alls

11. Hur bedömer du din körstil?

mycket defensiv mycket offensiv

12. Tänk på situationer i vilka du måste köra i några timmar utan att kunna ta en längre paus. Upplever du följande över tid?

a. komfort

minskar komfort ökar

b. ökad trötthet piggare

c. försämrad reaktionstid förbättrad

reaktionstid

d. försämrad koll på vägskyltar

bättre koll på vägskyltar

e. försämrad syn förbättrad syn

f. svårare att bedöma din hastighet

bättre hastighets-bedömning

g. körglädjen minskar körglädjen

ökar

h. körstilen blir djärvare körstilen blir

försiktigare

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VTI rapport 638A

Fp (P): __________ Datum: __________________

Erfarenheter

1. Hur tyckte du att du körde med den lånade bilen, jämfört med din egen bil?

Körde du med den lånade bilen …

likadant a. mindre

försiktigt mer försiktigt

b. oftare mer sällan

c. bättre sämre

d. med större glädje med mindre

glädje 2. Hur lång tid behövde du för att vänja dig vid bilen?

1 dag 2 dagar 3 dagar 4 dagar längre

Ytterligare kommentarer kring försöket:

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VTI rapport 638A

Inställningar

3. Tycker du allmänt sett att det är acceptabelt eller ej acceptabelt att …

acceptabelt ej acceptabelta. prata i telefon medan man

kör bil (handhållen)

b. prata i telefon medan man kör bil (handsfree)

c. köra bil när man är mycket trött

d. köra bil onykter

e. köra utan säkerhetsbälte

4. Tror du att följande system ökar eller sänker trafiksäkerheten?

trafiksäker-heten

sjunker mycket

ingen förändring

trafiksäker-heten

ökar mycket a. navigationssystem

b. kollisionsvarning

c. avåkningsvarning

d. distraktionsvarning

e. halkvarning

f. trötthetsvarning

5. Hur säkert tycker du att det är att släppa uppmärksamheten en stund för att göra något annat (prata i telefon, titta på kartan, byta musik, etc.) på följande vägtyper?

mycket säkert mycket

farligt a. i tätort (innerstaden)

b. i tätort (bostadsområde)

c. på 70-väg

d. på 90-väg

e. på 110-väg (ej motorväg)

f. på motorväg

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VTI rapport 638A

6. Hur ofta gör du följande när du kör bil?


a. pratar i telefon (handhållen)

b. pratar i telefon (handsfree)

c. äter/dricker

d. kammar mig, sminkar mig, rakar mig, etc.

e. röker

f. kollar i almanacka/ adressbok

g. byter kassettband/CD

h. läser en karta

i. annat: _________________

7. Hur ofta händer det när du kör bil att du …


a. är så pass distraherad att du inte uppfattar vad som hände de sista sekunderna och överraskas av situationen

b. är lite trött

c. är mycket trött

d. måste kämpa för att hålla dig vaken

e. kör långa sträckor utan paus

f. uppmärksammas på en trafikfara av en passagerare

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VTI rapport 638A

8. Vad distraherar dig när du kör bil?

Lämna öppet om ej relevant (t. ex. om du aldrig pratar i telefon). inte alls väldigt

mycket

a. prata i telefon (handhållen)

b. prata i telefon (handsfree)

c. vuxna passagerare (över 16 år)

d. passagerare som är barn (6-16 år)

e. passagerare som är barn (0-5 år)

f. ha svårigheter att hitta rätt

g. vacker omgivning

h. tråkig omgivning

i. reklam/affärer

j. annat: _________________

9. Distraheras du lättare när …

Lämna öppet om ej relevant (t. ex. om du aldrig kör med passagerare).

e. du är mycket trött du är mycket

pigg

f. du har kört en lång sträcka

du har enbart kört en kort sträcka

g. du är ensam i bilen du har

passagerare

h. du kör på bekanta vägar

du kör på obekanta vägar

i. det är mörkt ute det är ljust

ute

j. det är mycket trafik det är lite

trafik

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VTI rapport 638A

10. Hur stor är risken för trötthet på följande vägtyper? 10. Hur stor är risken för trötthet på följande vägtyper?

mycket liten

mycket liten mycket

stor mycket

stor g. g. i tätort (innerstaden) i tätort (innerstaden)

h. h. i tätort (bostadsområde) i tätort (bostadsområde)

i. i. på 70-väg på 70-väg

j. j. på 90-väg på 90-väg

k. k. på 110-väg (ej motorväg) på 110-väg (ej motorväg)

l. l. på motorväg på motorväg

5

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VTI rapport 638A

Förväntningar Distraktionsvarning

Tänk dig att du skulle få ett system som varnar när du är distraherad under bilkörningen. De följande frågor handlar om vad du skulle förvänta dig av ett sådant system.

11. Vilken är din spontana inställning till distraktionsvarningssystem?

mycket positiv mycket negativ

12. Hur stor nytta tror du att du skulle ha av ett distraktionsvarningssystem?

ingen nytta alls mycket stor nytta

13. Hur skulle du vilja att systemet varnar dig?

ja nej

a. med ett ljud (t. ex. ett pip)

b. med en blinkande lampa

c. med en röst som säger någonting

d. med en vibration i sätet

e. med en vibration i bältet

f. med en vibration i ratten

g. annat: _________________

14. I hur stor utsträckning tror du att varningarna skulle kännas onödiga?

aldrig alltid

15. Tror du att du skulle känna dig störd av ett distraktionsvarningssystem?

ja, ofta nej, aldrig

16. Hur pass mycket tror du att du skulle lita på ett distraktionsvarningssystem?

inte alls helt och hållet

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VTI rapport 638A

17. Hur tror du att följande faktorer skulle påverkas av ett distraktionsvarningssystem?

minskar mycket

minskar något

ingen förändring

ökar något

ökar mycket

a. din trafiksäkerhet

b. din komfort

c. din körglädje

d. din mobilitet

e. din restid

f. din stress

18. Kan du se några risker med distraktionsvarningssystem?

ja nej Om ja, beskriv:

7


VTI rapport 638A

Förväntningar Trötthetsvarning

Tänk dig att du skulle få ett system som varnar när du är för trött för att köra bil på ett säkert sätt, eftersom det finns en risk att du skulle kunna somna. De följande frågor handlar om vad du skulle förvänta dig av ett sådant system.

19. Vilken är din spontana inställning till trötthetsvarningssystem?


20. Hur stor nytta tror du att du skulle ha av ett trötthetsvarningssystem?


21. Hur skulle du vilja att systemet varnar dig?

ja nej

a. med ett ljud (t. ex. ett pip)

b. med en blinkande lampa

c. ett textmeddelande på instrumentbrädan

d. med en röst som säger någonting

e. en vibration i sätet

f. en vibration i bältet

g. en vibration i ratten

h. annat: _________________

22. I hur stor utsträckning tror du att varningarna skulle kännas onödiga?

aldrig alltid

23. Tror du att du skulle känna dig störd av ett trötthetsvarningssystem?


24. Hur pass mycket tror du att du skulle lita på ett trötthetsvarningssystem?


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VTI rapport 638A

25. Hur tror du att följande faktorer skulle påverkas av ett trötthetsvarningssystem?

minskar mycket

minskar något

ingen förändring

ökar något

ökar mycket

a. din trafiksäkerhet

b. din komfort

c. din körglädje

d. din mobilitet

e. din restid

f. din stress

26. Kan du se några risker med trötthetsvarningssystem?

ja nej Om ja, beskriv:

9


VTI rapport 638A

Fp (P): __________ Datum: __________________

Nu är din körning med den lånade bilen klar. I denna sista enkät ber vi dig att berätta hur du upplevde körningen och varningssystemen. Frågorna är inriktade på tiden som du hade lånat forskningsbilen och varningssystemen var påslagna.

Inställningar

1. Hur säkert tyckte du att det var att släppa uppmärksamheten en stund för att göra

något annat (prata i telefon, titta på kartan, byta musik, etc.) på följande vägtyper?

mycket säkert mycket

farligt a. i tätort (innerstaden)

b. i tätort (bostadsområde)

c. på 70-väg

d. på 90-väg

e. på 110-väg (ej motorväg)

f. på motorväg

2. Hur ofta gjorde du följande i den lånade bilen?


a. pratade i telefon (handhållen)

b. pratade i telefon (handsfree)

c. åt/drack

d. kammade mig, sminkade mig, rakade mig, etc.

e. rökte

f. kollade i almanacka/ adressbok

g. bytte kassettband/CD

h. läste en karta

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VTI rapport 638A

3. Hur ofta hände det när du körde den lånade bilen att du …


a. var så pass distraherad att du inte uppfattade vad som hände de sista sekunderna och överraskades av situationen

b. var lite trött

c. var mycket trött

d. fick kämpa för att hålla dig vaken

e. körde långa sträckor utan paus

f. uppmärksammades på en trafikfara av en passagerare

4. Vad distraherade dig när du körde den lånade bilen?

Lämna öppet om ej relevant (t. ex. om du aldrig pratade i telefon). inte alls väldigt

mycket

a. prata i telefon (handhållen)

b. prata i telefon (handsfree)

c. vuxna passagerare (över 16 år)

d. passagerare som är barn (6-16 år)

e. passagerare som är barn (0-5 år)

f. ha svårigheter att hitta rätt

g. vacker omgivning

h. tråkig omgivning

i. reklam/affärer

j. trötthetsvarningen

k. själva distraktionsvarningen

l. annat: _________________

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VTI rapport 638A

5. Distraherades du lättare när …

Lämna öppet om ej relevant (t. ex. om du aldrig körde med passagerare).

a. du var mycket trött du var

mycket pigg

b. du hade kört en lång sträcka

du hade kört en kort sträcka

c. du var ensam i bilen du hade

passagerare

d. du körde på bekanta vägar

du körde på obekanta vägar

e. det var mörkt ute det var ljust

ute

f. det var mycket trafik det var lite

trafik

3


VTI rapport 638A

Erfarenheter Distraktionsvarning

Nu har du provat ett distraktionsvarningssystem. De följande frågor handlar om hur du upplevde systemet.

6. Vilken är din spontana inställning till distraktionsvarningssystemet?


7. Fick du några distraktionsvarningar (inte medvetet provocerade)?

nej 1-5 5-20 20-100 över 100

Om du svarade ”nej”, vänligen fortsätt med fråga 15. 8. Hur stor nytta hade du av distraktionsvarningssystemet?


9. När tyckte du att varningen kom?

mycket för tidigt mycket för sent

10. I hur stor utsträckning kändes varningarna onödiga?

aldrig alltid

11. Kände du dig störd av distraktionsvarningssystemet?


12. Hur pass mycket litade du på distraktionsvarningssystemet?


4


VTI rapport 638A

13. Hade du hellre haft en annan typ av varning?

ja nej

a. ett ljud (t. ex. ett pip)

b. en blinkande lampa

c. en röst som säger någonting

d. en vibration i bältet

e. en vibration i ratten

f. f. annat: _________________ annat: _________________ 14. Hur påverkades följande faktorer av distraktionsvarningssystemet? 14. Hur påverkades följande faktorer av distraktionsvarningssystemet?

minskade mycket

minskade mycket

minskade något

minskade något

ingen förändring

ingen förändring

ökade ökade något något

ökade mycket ökade mycket

a. a. din trafiksäkerhet din trafiksäkerhet

b. b. din komfort din komfort

c. c. din körglädje din körglädje

d. d. din mobilitet din mobilitet

e. e. din restid din restid

f. f. din stress din stress

15. Kan du se några risker med distraktionsvarningssystem? 15. Kan du se några risker med distraktionsvarningssystem?

ja ja nej nej Om ja, beskriv: Om ja, beskriv:

16. Lista de tre bästa egenskaperna hos distraktionsvarningssystemet du provade

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VTI rapport 638A

17. Lista de tre sämsta egenskaperna hos distraktionsvarningssystemet du provade

18. Skulle du vilja ha ett sådant distraktionsvarningssystem eller något liknande i din

bil?

ja nej Motivera ditt svar:

Om ja, hur mycket skulle du kunna tänka dig betala för systemet? _______________ kr Ytterligare kommentarer kring distraktionsvarningssystemet:

6


VTI rapport 638A

Erfarenheter Trötthetsvarning

Nu har du provat ett trötthetsvarningssystem. De följande frågor handlar om hur du upplevde systemet.

19. Vilken är din spontana inställning till trötthetsvarningssystem?


20. Fick du några trötthetsvarningar (inte medvetet provocerade)?

nej ja, en ja, fler

a. på lägsta nivån (textdisplay)

b. på mellersta nivån (text och röst)

c. på högsta nivån (ljud, text och röst)

Om du svarade ”nej” på alla tre alternativ, vänligen fortsätt med fråga 28. 21. Hur stor nytta hade du av trötthetsvarningssystemet?


22. Vad tyckte du om utformingen av varningarna?

På lägsta varningsnivån:

mycket bra mycket

dåligt a. textmeddelandet var

På mellersta varningsnivån (fick ej denna varning fortsätt med fråga 23):

mycket bra mycket

dåligt b. textmeddelandet var

c. röstvarningen var

På högsta varningsnivån (fick ej denna varning fortsätt med fråga 23):

mycket bra mycket

dåligt d. textmeddelandet var

e. röstvarningen var

f. ljudvarningen var

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VTI rapport 638A

23. Var det bra att du kunde ”kvittera” varningarna?

ja nej fick ej

a. på lägsta nivån (textdisplay)

b. på mellersta nivån (text och röst)

c. c. på högsta nivån (ljud, text och röst) på högsta nivån (ljud, text och röst)

24. I hur stor utsträckning kändes varningarna onödiga? 24. I hur stor utsträckning kändes varningarna onödiga?

aldrig aldrig alltid alltid

25. Kände du dig störd av trötthetsvarningssystemet? 25. Kände du dig störd av trötthetsvarningssystemet?

ja, ofta ja, ofta nej, aldrig nej, aldrig

26. Hur pass mycket litade du på trötthetsvarningssystemet? 26. Hur pass mycket litade du på trötthetsvarningssystemet?

inte alls inte alls helt och hållet helt och hållet

27. Påverkades följande faktorer av trötthetsvarningssystemet? 27. Påverkades följande faktorer av trötthetsvarningssystemet?

minskade mycket

minskade mycket

minskade något

minskade något

ingen förändring

ingen förändring

ökade ökade något något

ökade mycket ökade mycket

a. a. din trafiksäkerhet din trafiksäkerhet

b. b. din komfort din komfort

c. c. din körglädje din körglädje

d. d. din mobilitet din mobilitet

e. e. din restid din restid

f. f. din stress din stress

28. Kan du se några risker med trötthetsvarningssystem? 28. Kan du se några risker med trötthetsvarningssystem?

ja ja nej nej Om ja, beskriv: Om ja, beskriv:

8


VTI rapport 638A

29. Lista de tre bästa egenskaperna hos trötthetsvarningssystemet du provade

30. Lista de tre sämsta egenskaperna hos trötthetsvarningssystemet du provade

31. Skulle du vilja ha ett sådant trötthetsvarningssystem eller något liknande i din bil?

ja nej Motivera ditt svar:

Om ja, hur mycket skulle du kunna tänka dig betala för systemet? _______________ kr Ytterligare kommentarer kring trötthetssvarningssystemet:

9


VTI rapport 638A

Ytterligare kommentarer kring hela försöket:

Stort tack för din medverkan!

10


VTI rapport 638A

VTI rapport 638A

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ler

inte

alls

och

mås

te la

gas

elle

r st

änga

s av

, vä

nlig

en k

onta

kta

förs

öksl

edni

ngen

på

följa

nde

tele

fonn

umm

er:

070–

869

44 7

1

Från

utla

ndet

rin

g:

+46-

70-8

69 4

4 71

Vikt

igin

form

atio

nD

et ä

r m

ycke

t vi

ktig

t at

t du

vet

att

ans

vare

t fö

r at

t fö

ra f

ram

bile

n på

ett

säk

ert

sätt

allt

id l

igge

r ho

s di

g.

10


VTI rapport 638A

Atte

nDA

ttenD

Atte

nD-S

yste

met

I den

na m

anua

l hitt

ar d

u in

form

atio

n om

dis

trak

tions

- oc

h tr

ötth

etsv

arn-

syst

emet

Att

enD

som

finn

s in

bygg

t i d

in b

il. B

åde

dist

rakt

ion

och

tröt

thet

vi

d bi

lkör

ning

lede

r til

l mån

ga t

ragi

ska

olyc

kor.

Att

enD

-sys

tem

et s

ka f

örbä

t-tr

a tr

afiks

äker

hete

n ge

nom

att

hjä

lpa

dig

att

uppt

äcka

när

du

är d

istr

aher

ad

elle

r tr

ött.

Hur

fung

erar

sys

tem

et?

Två

kam

eror

som

föl

jer

dina

huv

ud-

och

ögon

röre

lser

är

inby

ggda

i bi

len.

I sa

mve

rkan

med

någ

ra a

ndra

par

amet

er (t

. ex.

vilk

en v

äxel

och

vilk

en

hast

ighe

t du

kör

i) g

ör s

yste

met

en

bedö

mni

ng o

m d

u är

upp

mär

ksam

, di

stra

hera

d el

ler

tröt

t. N

är s

yste

met

det

ekte

rar

att

du ä

r di

stra

hera

d el

ler

tröt

t up

pmär

ksam

mar

sys

tem

et d

ig p

å de

tta.

Hur

det

går

till

bes

kriv

s ne

dan.

Dis

trak

tion

Det

kan

var

a fa

rlig

t at

t tit

ta b

ort

från

väg

en e

n lä

ngre

stu

nd. D

istr

aktio

ns-

varn

ings

syst

emet

hjä

lper

dig

att

det

ekte

ra n

är d

u ha

r tit

tat

bort

frå

n vä

gen

så p

ass

läng

e at

t de

t ka

n ut

göra

en

fara

. Båd

e nä

r du

titt

ar b

ort

från

väg

en

en lä

ngre

stu

nd o

ch n

är d

u up

prep

ade

gång

er b

licka

r bo

rt f

rån

väge

n ka

n va

ra f

arlig

a. S

yste

met

var

nar

dig

för

båda

.

När

kri

teri

et f

ör d

istr

aktio

n är

upp

nått

kom

mer

du

att

känn

a av

en

vi

brat

ion

i sät

et. D

ina

pass

ager

are

kom

mer

inte

att

mär

ka a

v va

rnin

gen.

Sä

tet

kom

mer

att

vib

rera

till

s du

titt

ar p

å vä

gen

igen

, men

ald

rig

läng

re ä

n tv

å se

kund

er. N

är d

u ha

r få

tt e

n di

stra

ktio

nsva

rnin

g ko

mm

er in

gen

ny

varn

ing

förr

än 1

5 se

kund

er h

ar g

ått

seda

n de

n se

nast

e bö

rjad

e.

Und

erv

ilka

föru

tsät

tnin

gar

fu

nger

ars

yste

met

?Fö

r at

t ku

nna

fung

era

mås

te s

yste

met

kun

na r

egis

trer

a di

na ö

gonr

örel

ser.

Som

”nö

dlös

ning

” ka

n sy

stem

et o

ckså

kän

na a

v åt

vilk

et h

åll d

itt h

uvud

är

vri

det.

Om

du

rör

dig

myc

ket

ur d

en n

orm

ala

sitt

posi

tione

n el

ler

om d

u sk

ymm

er d

elar

av

ditt

ans

ikte

med

han

den

elle

r nå

got

anna

t fö

rem

ål b

lir

bedö

mni

ngsk

valit

én s

ämre

elle

r de

tekt

erin

gen

slut

ar h

elt.

Om

du

titta

de

fram

åt n

är s

yste

met

tap

pade

kon

takt

ligg

er d

en r

egis

trer

ade

dist

rakt

ions

-ni

vån,

som

ber

äkna

ts in

nan

syst

emet

tap

pat

kont

akt,

kvar

till

s tr

acki

ngen

åt

erup

ptas

. Ann

ars

anta

r sy

stem

et a

tt d

u tit

tar

bort

och

du

kan

få e

n

varn

ing.

Det

kan

allt

så h

ända

att

du

inte

får

någ

on v

arni

ng ä

ven

om d

u ha

r va

rit

myc

ket

dist

rahe

rad.

Den

reg

istr

erad

e tr

ötth

etsn

ivån

som

ber

äkna

ts

inna

n sy

stem

et t

appa

t ko

ntak

ten

ligge

r kv

ar t

ills

trac

king

en å

teru

ppta

s.

För

att

säke

rstä

lla a

tt s

yste

met

kan

fun

gera

så

bra

som

möj

ligt

är d

et v

iktig

t at

t du

i s

å st

or u

tstr

äckn

ing

som

möj

ligt

kör

med

sam

ma

inst

älln

ing

fö

r sä

tet

På

det

vis

et k

an s

yste

met

föl

ja d

in b

lickr

iktn

ing

på b

ästa

sät

t.

D

in ins

tälln

ing

är p

rogr

amm

erat

på

plat

s 3

vid

säte

t; try

ck p

å

”3”

tills

sto

len

slut

ar r

öra

på s

ig.

av

står

frå

n at

t an

vänd

a so

lgla

sögo

n.

D

e fö

rsäm

rar

ögon

trac

king

en a

vsev

ärt.

Speg

land

e

gl

asög

on f

örhi

ndra

r tr

acki

ngen

hel

t.

Trac

king

profi

len

är p

erso

nbun

den.

Den

är

anpa

ssad

så

att

den

fung

erar

på

bäst

a m

öjlig

a sä

tt p

å en

per

son.

Om

någ

on a

nnan

per

son

kör

bile

n ko

mm

er

syst

emet

att

ha

dålig

tra

ckin

g, o

ch d

å ka

n m

an f

å m

ånga

fel

varn

inga

r el

ler,

om t

rack

inge

n in

te f

unge

rar

över

huvu

dtag

et, i

nga

varn

inga

r al

ls.

Vikt

igin

form

atio

nSy

stem

et m

edde

lar

dig

när

du h

ar t

ittat

bor

t fr

ån

väge

n en

läng

re s

tund

. Det

ta in

nebä

r in

te a

tt d

et ä

r sä

kert

att

titt

a bo

rt ti

lls d

u få

r en

var

ning

. Sys

tem

et

kan

inte

bed

öma

trafi

ken,

väd

erfö

rhål

land

en e

ller

vägm

iljön

!

58


VTI rapport 638A

Atte

nDA

ttenD

Snab

bgui

de

Tills

tånd

Varn

ing

Rek

omen

dera

dåt

gärd

dist

rahe

rad

vibr

atio

nis

ätet

titta

tillb

aka

påv

ägen

förs

tate

cken

på

tröt

thet

ton

+te

xtm

edde

land

elå

tnåg

ona

nnan

kör

a

tae

npa

us,e

ntu

pplu

r

och

enk

opp

kaffe

stan

nao

chs

ov

tröt

tto

n+

text

med

dela

nde

röst

insp

elni

ng

myc

kett

rött

elle

r

har

som

nat

högl

judd

var

ning

text

med

dela

nde

röst

insp

elni

ng

11


VTI rapport 638A

Atte

nDA

ttenD

Und

erv

ilka

föru

tsät

tnin

gar

får

jag

inga

dis

trak

tions

varn

inga

r?Sy

stem

et k

an in

te g

öra

bedö

mni

ngar

av

trafi

ksitu

atio

nen,

väd

erfö

rhål

land

en

elle

r vä

gmilj

ön, m

en d

et h

ar t

illgå

ng t

ill e

n de

l inf

orm

atio

n so

m k

omm

er

dire

kt f

rån

bile

n. F

ör a

tt m

insk

a an

tale

t fe

lvar

ning

ar s

täng

s va

rnin

garn

a av

he

lt un

der

följa

nde

betin

gels

er. D

u ko

mm

er a

ldri

g at

t få

en

varn

ing

när

ha

stig

hete

n är

min

dre

än 5

0 km

/h

N

är m

an k

ör s

akta

kan

det

finn

as s

käl f

ör a

tt m

an t

itta

r bo

rt f

rån

väge

n en

läng

re s

tund

uta

n at

t m

an b

ehöv

er v

ara

dist

rahe

rad.

ba

ckvä

xeln

ligg

er i

N

är m

an b

acka

r sk

a m

an t

itta

bak

åt.

bl

inke

rs ä

r ak

tiver

ade.

V

id k

örfä

ltsby

ten

och

i ku

rvor

är

det

nödv

ändi

gt a

tt s

öka

av d

et

om

ligga

nde

områ

det.

9


VTI rapport 638A

Atte

nDA

ttenD Tr

ötth

etG

enom

att

obs

erve

ra h

ur m

ycke

t oc

h hu

r lä

nge

du b

linka

r m

ed ö

gone

n oc

h om

din

a ög

onlo

ck

är ”

tung

a” b

edöm

er s

yste

met

om

du

är t

rött

el

ler

inte

. Sys

tem

et g

ör e

n ny

bed

ömni

ng v

ar

30:e

sek

und.

Sys

tem

et s

kilje

r på

föl

jand

e

tills

tånd

:

Tröt

thet

sniv

åSy

stem

med

dela

nde

Kon

firm

atio

nÅ

tgär

dD

uär

pig

g.Sy

stem

etg

erin

gen

in

form

atio

n.

Du

börj

arb

litr

ött,

men

du

kom

mer

at

tkun

nah

ålla

dig

va

ken

enlä

ngre

st

und

fram

över

.

Efte

ret

tpip

kom

mer

sys

tem

et

attp

rese

nter

aet

ttex

tmed

-de

land

epå

mitt

kons

olen

:”T

rött?

”Med

dela

ndet

slo

ckna

ref

ter

ens

tund

elle

rom

du

tryc

ker

påd

enr

öda

knap

pen

för

konfi

rmat

ion

och

visa

sig

ene

fter

tidig

ast3

0m

inut

er

ifall

atts

amm

atr

ötth

etsn

ivå

före

ligge

r.

Om

du

tryc

ker

påd

en

röda

kon

firm

atio

ns-

knap

pen

sloc

knar

med

-de

land

eto

chv

isas

igen

ef

ter

tidig

ast3

0m

inut

er

ifall

atts

amm

atr

ötth

ets-

nivå

före

ligge

r.

Om

det

är

möj

ligt,

låt

någo

nan

nan

som

är

m

indr

etr

öttk

öra

bile

n.

Om

den

nam

öjlig

het

inte

finn

sär

den

end

am

öjlig

hete

nat

tbek

ämpa

tr

ötth

ete

ffekt

ivta

ttso

va.

Har

du

inte

möj

lighe

tatt

sova

ord

entli

gtk

and

uta

en

tupp

lur

på1

0m

inut

er.H

ur

läng

edu

kan

fort

sätta

med

at

tkör

abi

lsed

anb

eror

på

hur

myc

ketd

uso

vna

tten

inna

noc

hen

del

and

ra

fakt

orer

.

Kaf

feo

cha

ndra

kof

fein

-ha

ltiga

dry

ckk

anu

nder

vi

ssa

omst

ändi

ghet

er

hjäl

pad

ige

nlit

ens

tund

.

OB

S:Å

tgär

der

som

att

öppn

asi

doru

tan,

höj

apå

ra

diov

olym

en,s

tann

aen

st

und

utan

att

sova

etc

.är

inge

nef

fekt

ivs

ömn-

bekä

mpn

ing.

Du

ärm

ycke

ttrö

tt.En

insp

elni

nga

ven

rös

tkom

-m

era

ttsä

ga”D

uär

för

tröt

tför

at

tkör

a!”D

etta

med

dela

nde

uppr

epas

en

gång

im

inut

en.

Des

suto

mp

iper

sys

tem

eto

ch

disp

laye

nvi

sar

text

med

dela

n-de

t:“D

uär

tröt

t!”

Om

du

tryc

ker

påd

en

röda

kon

firm

atio

ns-

knap

pen

pres

ente

ras

va

rnin

gen

igen

efte

rtid

igas

t5m

inut

ero

m

sam

ma

elle

ren

lägr

etr

ötth

etsn

ivå

före

ligge

r.

Du

ärn

ära

att

som

nae

ller

har

som

nat.

Syst

emet

ger

ett

högt

,pip

ande

lju

difr

åns

ig.P

ådi

spla

yen

visa

s:”D

uso

mna

rsn

art!”

och

rö

stin

spel

ning

ens

äger

:”D

uär

fa

rlig

ttrö

tt,s

tann

asn

aras

t!”

Om

du

tryc

ker

påd

en

röda

kon

firm

atio

ns-

knap

pen

pres

ente

ras

varn

inge

nig

ene

fter

tidig

ast5

min

uter

om

sa

mm

ael

ler

enlä

gre

tröt

thet

sniv

åfö

relig

ger.

Kon

firm

atio

nskn

app

Vikt

igin

form

atio

nSy

stem

et m

edde

lar d

ig n

är d

u ve

rkar

var

a tr

ött.

Det

är

ille

galt

att

köra

bil

i tr

ött

tills

tånd

. D

et fi

nns

inge

n ga

rant

i at

t du

kan

hål

la d

ig v

aken

till

s du

få

r va

rnin

gen

på n

ivå

4. S

yste

met

är

inge

n vä

ck-

arkl

ocka

so

m

kan

väck

a di

g i

tid.

Gen

om

att

mis

sbru

ka s

yste

met

som

såd

an s

ätte

r du

ditt

och

an

dras

liv

på

spel

. Se

till

att

vila

när

du

känn

er

att

du b

ehöv

er d

et, o

ch s

enas

t nä

r du

får

en

varn

-in

g på

niv

å 2.

Om

du

känn

er a

tt d

u be

höve

r vi

la

inna

n sy

stem

et v

arna

r di

g, s

å gö

r de

t! V

änta

int

e in

var

ning

en!

67

1 2 3 4


VTI rapport 638A

Technical data

Technical data Watec WAT 902H


VTI rapport 638A

Technical Data Heitel


VTI rapport 638A

Technical Data GPS receiver


VTI rapport 638A

GPS NMEA Sentence description


VTI rapport 638A

Technical Data VGA-FBAS video converter


VTI rapport 638A

VTI rapport 638A

Variables saved in text files listed for all six modules, with a description of the triggers saved

Warning Control Module

Variable Name Description unit / range

TimeStamp coarse time stamp, same in all modules

hh:mm:ss

FineTimeStamp

ms from computer start, same start in all modules

ms

Trigger bit coded trigger 0-255

Triggers for Warning Control Module

bit description state when bit position equals 1

1 Inhibited Attention Warning

On

2 Inhibited Drowsiness Warning

On

4 Attention Buffer is 0 0

8 Drowsiness Classified As Level 1



64 VF Display error

128 Drowsiness Confirm Button Pressed

SE Raw Module



hh:mm:ss

FineTimeStamp


ms


Zone1 first intersection between gaze

0-16


VTI rapport 638A

direction and a world zone (see Chapter 5.1)

Zone2

second intersection between gaze direction and a world zone

0-16

EyeOpening

distance between upper and lower lid in m

m

EyeOpeningQ quality of EyeOpening

[0; 1]

HeadPosX head position in x-direction

[-1; 1]

HeadPosY head position in y-direction

[-1; 1]

HeadPosZ head position in z-direction

[-1; 1]

HeadPosQ quality of head position

0: no camera detects head

0.5: one camera detects head

1: two cameras detect head

EyePosX eye position in x-direction

[-1; 1]

EyePosY eye position in y-direction

[-1; 1]

EyePosZ eye position in z-direction

[-1; 1]

GazeDirX gaze direction in x-direction

[-1; 1]

GazeDirY gaze direction in y-direction

[-1; 1]

GazeDirZ gaze direction in z-direction

[-1; 1]

GazeDirQ quality of gaze direction value

[0; 1]

NoseDirX nose direction in x-direction

[-1; 1]

NoseDirY nose direction in y-direction

[-1; 1]

NoseDirZ nose direction in z-direction

[-1; 1]

Triggers SE Raw Module


VTI rapport 638A


1 Too Low Gaze Quality

< 0.2

2 Too Low Eyelid Quality

< 0.2

4 Too Low HeadPosition Quality

<.05

8 Corrupt SmartEye Data

16

32

64

128

Drowsy Log Module



hh:mm:ss

FineTimeStamp


ms


RightEyeLidO opening between right eye lids

m

LeftEyeLidO opening between left eye lids

RightEyeLidQ quality of RightEyeLidO value

LeftEyeLidQ quality of LeftEyeLidO value

TimingHour

hour from log start, input to drowsy algorithm

TimingMinute

minute from log start, input to drowsy algorithm

EyeLidTimeSec

second from log start, input to drowsy algorithm

EyeLidTimeMS

ms from log start, input to drowsy algorithm


VTI rapport 638A

DrowsyLevel

drowsy level output between alert and very drowsy

0, 1, 2, 3

DrowsyConfidence confidence value for DrowsyLevel

Triggers Drowsy Log Module


1 Too low left eyelid quality

< 0.2

2 Too low right eyelid quality

< 0.2

4 Corrupt SmartEye Data

8 Too low quality for algorithm




128

IDP-Module



hh:mm:ss

FineTimeStamp ms from computer start, same start in all modules

ms


Zone1 first intersection between gaze direction and a world zone (see Chapter 5.1)

0-16

Zone2 second intersection between gaze direction and a world zone

0-16


VTI rapport 638A

EyeOpening distance between upper and lower lid in m

m

EyeOpeningQ quality of EyeOpening

[0; 1]

HeadPosX head position in x-direction

[-1; 1]

HeadPosY head position in y-direction

[-1; 1]

HeadPosZ head position in z-direction

[-1; 1]

HeadPosQ

quality of head position

0: no camera detects head

0.5: one camera detects head

1: two cameras detect head

EyePosX eye position in x-direction

[-1; 1]

EyePosY eye position in y-direction

[-1; 1]

EyePosZ eye position in z-direction

[-1; 1]

GazeDirX gaze direction in x-direction

[-1; 1]

GazeDirY gaze direction in y-direction

[-1; 1]

GazeDirZ gaze direction in z-direction

[-1; 1]

GazeDirQ quality of gaze direction value

[0; 1]

NoseDirX nose direction in x-direction

[-1; 1]

NoseDirY nose direction in y-direction

[-1; 1]

NoseDirZ nose direction in z-direction

[-1; 1]

SteeringWheel

AttentionBuffer current status of the attention buffer

[0; 2]

TwoInSix accumulated time during which the participant looked away from the FRD within the last 6 s

[0; 6]

Confidence confidence value


VTI rapport 638A

Triggers IDP Module


1 Attention Buffer is 0 0

2 Two In Six “Warning” 2 s

4

8 Gaze Outside Of VFRD

16 Head Direction Outside of HFRD

32 No Tracking

64

128

In/Out-Module



hh:mm:ss

FineTimeStamp


ms


DigitalIn

DigitalOut

Triggers In/Out-Module


1 port 0: Vibrator on

2 port 1: Vibrator (två portar krävdes för att inte överskrida strömbegränsningen)

on

4 port 2-5: Video triggers (2-4 har triggats felaktigt varje gång vibratorpuckarna vibrerat)

on


VTI rapport 638A

8

16

32

64 port 6:mute (används ej än)

128 port 7: Hardware watchdog

CAN-Module



hh:mm:ss

FineTimeStamp


ms


SteeringWheel

steering wheel angle in degrees, negative values denote curve to the left, positive values denote curve to the right

ca. [-500; 500]

Accelerator

percentage of accelerator depression

[0; 100]

BrakePedal brake force in kPa

Gear

actual gear number 0: during gear change

1-6: gear

8: reverse

9: neutral

10: park

ABS abs active 0; 1

ABSFailure abs system failed

LateralAcceleration

lateral acceleration in m/s2, left curve: positive values; right curve: negative values

CruiseControl cruise control on/off

HighBeam high beam on/off

LowBeamSwitch low beam on/park lights/off


VTI rapport 638A

TurnSwitch turn indicator left/right/off

1; 2; 0

Odometer totral driven distance km

InsideTemperatur temperature inside of compartment

°C

OutsideTemperature

temperature as measured by outside sensor

°C

Speed vehicle speed km/h

WindshieldWiper different positions of windscreen wipers

YawRate yaw rate

DriverSeatbelt driver seatbelt attached yes/no

Passenger passenger seat occupied

0; 1

DisplayDimming

Battery battery voltage

LongitudinalAcceleration

longitudinal acceleration as computed from speed (not on CAN)

Triggers CAN-Module


1 ABS active On

2

4

8

16 Longitudinal Acceleration

> 5 m/s^2 Calculated value

32 Lateral Acceleration > 5 m/s^2

64 ABS failed On

128 Yaw Rate > 35 deg/s


VTI rapport 638A

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distraction and drowsiness – a field...

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