Av resultaten från denna enkät är något av det mest tydliga att saker som funnits i en bil en längre tid, exempelvis att ställa in radio, använda navigationsutrustning och prata i telefon, görs i betydligt högre utsträckning än nyare saker som att skicka meddelanden, surfa på internet eller spela spel. Överlag tycks det vara låg acceptans för de nyare företeelserna och en stor andel av urvalet tycker att det är felaktigt eller olämpligt att hålla på med dessa aktiviteter. Att prata i telefon med handsfree tycks uppfattas av många som säkrare och mer lämpligt än att inte använda det. Detta avspeglas även i inställning till införandet av förbud, där en relativt stor andel accepterar att det ska vara lagligt att använda handsfreefunktioner men att annan användning av kommunikationsutrustning borde förbjudas.

I den andra delen genomfördes en mätning av mobilanvändning under färd genom installerande tav en mobilapp. Den genomförda undersökningen är den första av sitt slag åtminstone i Sverige, så att den, trots vissa brister och begränsningar, kan leverera information som hittills har varit okänt. I detta del diskuteras resultaten, även i förhållande till enkätsvaren, följt av en reflektion över metoden och möjliga förbättringar, som är önskvärda inför en fortsättningsstudie.

Indicators based on visual time-sharing have been used to investigate drivers' visual behaviour during additional task execution. However, visual time-sharing analyses have been restricted to additional tasks with well-defined temporal start and end points and a dedicated visual target area. We introduce a method to automatically extract visual time-sharing sequences directly from eye tracking data. This facilitates investigations of systems, providing continuous information without well-defined start and end points. Furthermore, it becomes possible to investigate time-sharing behavior with other types of glance targets such as the mirrors. Time-sharing sequences are here extracted based on between-glance durations. If glances to a particular target are separated by less than a time-based threshold value, we assume that they belong to the same information intake event. Our results indicate that a 4-s threshold is appropriate. Examples derived from 12 drivers (about 100 hours of eye tracking data), collected in an on-road investigation of an in-vehicle information system, are provided to illustrate sequence-based analyses. This includes the possibility to investigate human-machine interface designs based on the number of glances in the extracted sequences, and to increase the legibility of transition matrices by deriving them from time-sharing sequences instead of single glances. More object-oriented glance behavior analyses, based on additional sensor and information fusion, are identified as the next future step. This would enable automated extraction of time-sharing sequences not only for targets fixed in the vehicle's coordinate system, but also for environmental and traffic targets that move independently of the driver's vehicle.

While in-vehicle eco-driving support systems have the potential to reduce greenhouse gas emissions and save fuel, they may also distract drivers, especially if the system makes use of a visual interface. The objective of this study is to investigate the visual behaviour of drivers interacting with such a system, implemented on a five-inch screen mounted above the middle console. Ten drivers participated in a real-world, on-road driving study where they drove a route nine times (2 pre-baseline drives, 5 treatment drives, 2 post-baseline drives). The route was 96 km long and consisted of rural roads, urban roads and a dual-lane motorway.

The results show that drivers look at the system for 5–8% of the time, depending on road type, with a glance duration of about 0.6 s, and with 0.05% long glances (>2s) per kilometre. These figures are comparable to what was found for glances to the speedometer in this study. Glance behaviour away from the windscreen is slightly increased in treatment as compared to pre- and post-baseline, mirror glances decreased in treatment and post-baseline compared to pre-baseline, and speedometer glances increased compared to pre-baseline. The eco-driving support system provided continuous information interspersed with additional advice pop-ups (announced by a beep) and feedback pop-ups (no auditory cue). About 20% of sound initiated advice pop-ups were disregarded, and the remaining cases were usually looked at within the first two seconds. About 40% of the feedback pop-ups were disregarded. The amount of glances to the system immediately before the onset of a pop-up was clearly higher for feedback than for advice.

The prevalence of mobile phone usage in traffic has been studied by road-side counting, naturalistic driving data, surveillance cameras, smartphone logging, and subjective estimates via surveys. Here, we describe a custom-made smartphone logging application along with suggestions on how future such applications should be designed. The developed application logs’ start and end times of all phone interactions (mobile phone applications, incoming/outgoing phone calls and text messages, audio output, and screen activations). In addition, all movements are automatically classified into transport, cycling, walking, running, or stationary. The capabilities of the approach are demonstrated in a pilot study with 143 participants. Examples of results that can be gained from smartphone logging include prevalence in different transportation modes (here found to be 12% while driving, 4% while cycling, and 7% while walking), which apps are being used (here found to be 19% navigation, 12% talking, 12% social media, and 10% games) and on which road types (rural, urban, highway etc.). Smartphone logging was found to be an insightful complement to the other methods for assessing phone use in traffic, especially since it allows the analyses of which apps are used and where they are used, split into transportation mode and road type, all at a relatively low cost.

The ability to assess the current attentional state of the driver is important for many aspects of driving, not least in the field of automation. Knowledge about the driver’s attentional state is necessary for the assessment of the effects of additional tasks on attention, and for the transfer of control between vehicle and driver. Therefore, different methods that can be used to assess attention, were evaluated theoretically and then empirically in a controlled field study and in the laboratory.

Six driving instructors participated in all experimental conditions of the study, delivering within-subjects data for all tested methods. Additional participants were recruited for some of the conditions. The test route consisted of 14 km of motorway with low to moderate traffic, which was driven three times per participant per condition. The on-road conditions were: baseline, driving with eye tracking and self-paced visual occlusion, and driving while thinking aloud. The laboratory conditions were: Describing how attention should be distributed on a motorway, giving a written percentage distribution for a motorway situation, and thinking aloud while watching a video from the baseline drive. For the analysis the on-road data were split into manoeuvres. Attention was distributed differently depending on manoeuvre type, which was evident from both eye tracking, occlusion, the think aloud protocol and the lab-based methods, therefore it is recommended to consider the type of manoeuvre when making attention assessments. The visual occlusion method is a valuable tool to assess spare visual capacity. Especially in combination with eye tracking, and in comparison with “baseline” driving it shows which glances are experienced as containing necessary information, and which glances are “spare” glances. The think aloud method is a meaningful tool to approach the driver’s actual mental representation of the situation at hand. However, this method should be used with caution, as talking about one’s attentional distribution in fact changes one’s glance behaviour in comparison to baseline driving. Expert judgements in the laboratory did not turn out to be a reliable and useful method for the assessment of drivers’ attentional distribution in traffic. This may be due to difficulties in verbally accessing procedural knowledge.

For successful attention assessment in a dynamic traffic situation it is important to have access to information about the manoeuvres made by the driver in relation to other vehicles on the road. Also, knowledge about the road layout, speed limit etc. should be incorporated into the assessment. All this requires a rather advanced instrumentation of the experimental vehicle. In addition, data reduction, analysis and interpretation are demanding. To summarise, driver attention assessment in real traffic is a complex task, but a triangulation of visual occlusion, eye tracking and thinking aloud is a promising combination of methods to come further on the way.

The ability to assess the current attentional state of the driver is important for many aspects of driving, not least in the field of partial automation for transfer of control between vehicle and driver. Knowledge about the driver's attentional state is also necessary for the assessment of the effects of additional tasks on attention. The objective of this paper is to evaluate different methods that can be used to assess attention, first theoretically, and then empirically in a controlled field study and in the laboratory.

Six driving instructors participated in all experimental conditions of the study, delivering within-subjects data for all tested methods. Additional participants were recruited for some of the conditions. The test route consisted of 14. km of motorway with low to moderate traffic, which was driven three times per participant per condition. The on-road conditions were: baseline, driving with eye tracking and self-paced visual occlusion, and driving while thinking aloud. The laboratory conditions were: Describing how attention should be distributed on a motorway, and thinking aloud while watching a video from the baseline drive.

The results show that visual occlusion, especially in combination with eye tracking, was appropriate for assessing spare capacity. The think aloud protocol was appropriate to gain insight about the driver's actual mental representation of the situation at hand. Expert judgement in the laboratory was not reliable for the assessment of drivers' attentional distribution in traffic. Across all assessment techniques, it is evident that meaningful assessment of attention in a dynamic traffic situation can only be achieved when the infrastructure layout, surrounding road users, and intended manoeuvres are taken into account. This requires advanced instrumentation of the vehicle, and subsequent data reduction, analysis and interpretation are demanding. In conclusion, driver attention assessment in real traffic is a complex task, but a combination of visual occlusion, eye tracking and thinking aloud is a promising combination of methods to come further on the way. .

Objective: To propose a driver attention theory based on the notion of driving as a satisficing and partially self-paced task and, within this framework, present a definition for driver inattention.

Background: Many definitions of driver inattention and distraction have been proposed, but they are difficult to operationalize, and they are either unreasonably strict and inflexible or suffer from hindsight bias.

Method: Existing definitions of driver distraction are reviewed and their shortcomings identified. We then present the minimum required attention (MiRA) theory to overcome these shortcomings. Suggestions on how to operationalize MiRA are also presented.

Results: MiRA describes which role the attention of the driver plays in the shared "situation awareness of the traffic system." A driver is considered attentive when sampling sufficient information to meet the demands of the system, namely, that he or she fulfills the preconditions to be able to form and maintain a good enough mental representation of the situation. A driver should only be considered inattentive when information sampling is not sufficient, regardless of whether the driver is concurrently executing an additional task or not.

Conclusions: The MiRA theory builds on well-established driver attention theories. It goes beyond available driver distraction definitions by first defining what a driver needs to be attentive to, being free from hindsight bias, and allowing the driver to adapt to the current demands of the traffic situation through satisficing and self-pacing. MiRA has the potential to provide the stepping stone for unbiased and operationalizable inattention detection and classification.

Objective: To investigate the extent of a driver's mental model with irrevocable visual occlusion and analysing the distance to crash.

Background: Drivers have a mental model of the immediate surroundings which allows them to predict their own as well as others' travel paths. To navigate safely through traffic, this mental model has to be updated frequently to remain valid. In between information sampling events, the mental model will become outdated over time, as the traffic system is dynamic.

Method: A simulator study with 22 participants was conducted to investigate the information decay in the mental model. This was implemented by extending visual occlusion until the driver collided with another vehicle or ran off the road, thus providing an estimate of how long it takes until the mental model becomes obsolete.

Results: An analysis of variance with the factors curve direction, curve radius and traffic showed that curve radius did not influence the distance to crash. Without traffic, drivers veered off the road sooner in right curves. Adding traffic eliminated this difference. Traffic ahead led to a shortened distance to crash. Compared to a tangential travel path from the current lateral position at the time of the occlusion, drivers crashed on average 2.6 times later than they would have, had they not had any mental model of the situation.

Conclusions: The drivers' mental representation of the future situation seems to include information on how to act, to alleviate deviations in yaw angle, including and considering the presence of other road users.

Semi-controlled studies provide a hybrid approach in between controlled experiments and naturalistic driving studies. As in controlled experiments, the researcher can assign participants to groups, select the route and define the tasks, but the participants are given more freedom when it comes to if, when, where and how to perform the tasks. Increased flexibility makes it possible to investigate how drivers use tactical behaviour to accommodate task execution. The disadvantage is decreased control and more complicated analyses.

The main objective of this paper is to discuss how to analyse data obtained in semi-controlled studies.The analysis of data from a semi-controlled study include three types of variables:

• variables that describe the experimental design
• variables that describe the tactical choices of the participants
• operational variables such as speed, lateral position or glance behaviour

To analyse the three types of variables a two-step procedure is suggested. First, the tactical indicators are analysed with regard to the experimental design. Second, the operational indicators are analysed and the tactical indicators are used to divide participants into sub-populations.

The semi-controlled design does not need any new statistical procedures to be developed. It is more important that the analysis conditions on the initial properties and not on structures that happen to occur during the experiment, like where the participant chose to do a certain task.We recommend to use the semi-controlled study method when investigating questions involving adaptive and compensatory behaviour on the tactical level. It is especially useful if causal relationships are of interest, if the data collection should be accelerated in comparison to naturalistic studies, and if certain geographical locations definitely should be included.

Bicyclists are a heterogeneous group, with varying abilities, traffic education and experience. While efficiency was identified as an important factor on utility bicycle trips, it might be traded for experienced safety, for example by choosing different pathways in a given situation, or by relinquishing one's right of way. In a semi-controlled study with 41 participants, a grouping was made according to self-reported riding speed in relation to other cyclists. The participants cycled twice along a 3 km inner-city route, passing four intersections with different priority rules. The cyclists were free to choose how to negotiate the intersections. Speed and the traffic surroundings were recorded via gps and cameras on the bike of the participant and of a following experimenter. For each cyclist, the ‘base’ speed on undisturbed segments was determined as reference. Based on this, the efficiency in different types of intersections was computed per cyclist group. It turned out that infrastructural aspects, cyclist group and the presence and behaviour of interacting traffic influenced cyclist efficiency. Faster cyclists were delayed more when the infrastructure required a stop regardless of the traffic situation, like at a red traffic light or a stop sign. The members of the so-called ‘comfort cyclists’ group were delayed the most in a roundabout with mixed traffic, where many chose to get off their bike and walk. In a society working for equality of access to the transport system, it is recommended to develop solutions that consider and accommodate the behaviours of different cyclist groups when planning bicycling infrastructure.

Objective: The present study strove to distinguish traffic-related glances away from the forward roadway from non-traffic-related glances while assessing the minimum amount of visual information intake necessary for safe driving in particular scenarios.

Background: Published gaze-based distraction detection algorithms and guidelines for distraction prevention essentially measure the time spent looking away from the forward roadway, without incorporating situation-based attentional requirements. Incorporating situation-based attentional requirements would entail an approach that not only considers the time spent looking elsewhere but also checks whether all necessary information has been sampled.

Method: We assess the visual sampling requirements for the forward view based on 25 experienced drivers’ self-paced visual occlusion in real motorway traffic, dependent on a combination of situational factors, and compare these with their corresponding glance behavior in baseline driving.

Results: Occlusion durations were on average 3 times longer than glances away from the forward roadway, and they varied substantially depending on particular maneuvers and on the proximity of other traffic, showing that interactions with nearby traffic increase perceived uncertainty. The frequency of glances away from the forward roadway was relatively stable across proximity levels and maneuvers, being very similar to what has been found in naturalistic driving.

Conclusion: Glances away from the forward roadway proved qualitatively different from occlusions in both their duration and when they occur. Our findings indicate that glancing away from the forward roadway for driving purposes is not the same as glancing away for other purposes, and that neither is necessarily equivalent to distraction.

Hur cyklister interagerar med infrastrukturen, och hur de integrerar utförandet av extrauppgifter, hänger ihop med den omgivande trafiksituationen och cyklistens egenskaper. För att studera sambanden närmare utfördes en semi-kontrollerad fältstudie med 41 cyklister, som tillhörde olika cyklistgrupper med avseende på deras vanliga hastighet under transportresor. Hastighet, blickriktning och taktiskt beteende som spårval och interaktion med inkommande textmeddelanden loggades, medan cyklisterna tillryggalade en sträcka i innerstaden på 6 kilometer. Intervjuer och tänka-högt protokoll samt filmning från olika perspektiv användes också.

Det var vanligt för cyklister att ignorera inkommande textmeddelanden, en tredjedel besvarades direkt under cykling. De textmeddelanden som hanterades under cykling ledde inte till ökade brister i uppmärksamhet eftersom cyklisterna anpassade hanterandet efter omgivningen. Interaktionen med telefonen skilde sig inte nämnvärt mellan cyklistgrupperna. Däremot påverkade infrastrukturen de olika cyklisttyperna på olika sätt, där snabbare cyklister upplevde en större fördröjning, där infrastrukturen tvingar fram stopp, medan komfortcyklister fördröjdes mest i en otydligt utformad cirkulationsplats. Det kom även fram att trottoarcykling är vanligt förekommande och främst ett uttryck av upplevd osäkerhet i blandtrafik med bilar. Det är alltså viktigt att ta hänsyn till olika behov bland cyklisterna när infrastruktur utformas, så att inga irritationer, osäkerheter eller konflikter uppstår.

Objective: To assess the attentional demand of different contextual factors in driving.

Background: The attentional demand on the driver varies with the situation. One approach for estimating the attentional demand, via spare capacity, is to use visual occlusion.

Method: Using a 3 × 5 within-subjects design, 33 participants drove in a fixed-base simulator in three scenarios (i.e., urban, rural, and motorway), combined with five fixed occlusion durations (1.0, 1.4, 1.8, 2.2, and 2.6 s). By pressing a microswitch on a finger, the driver initiated each occlusion, which lasted for the same predetermined duration within each trial. Drivers were instructed to occlude their vision as often as possible while still driving safely.

Results: Stepwise logistic regression per scenario indicated that the occlusion predictors varied with scenario. In the urban environment, infrastructure-related variables had the biggest influence, whereas the distance to oncoming traffic played a major role on the rural road. On the motorway, occlusion duration and time since the last occlusion were the main determinants.

Conclusion: Spare capacity is dependent on the scenario, selected speed, and individual factors. This is important for developing workload managers, infrastructural design, and aspects related to transfer of control in automated driving.

Application: Better knowledge of the determinants of spare capacity in the road environment can help improve workload managers, thereby contributing to more efficient and safer interaction with additional tasks.

Cyclists' use of mobile phones in traffic has typically been studied in controlled experiments. How cyclists adapt their behaviour when they are not limited to a certain set of behaviours has not been investigated to any large extent. The aims of this study are to explore how cyclists adapt when texting and listening to music in a complex urban environment, and if they compensate sufficiently to maintain safe traffic behaviour. Forty-one cyclists participated in a semi-controlled study, using their own bike and smartphone in real traffic. They were equipped with eye tracking glasses and travelled two laps completing a total of 6 km divided into six segments. For one of the laps, the cyclists were requested to listen to music. On three occasions, they received a text message to their phone, which they were supposed to handle as they normally would when cycling. Static minimum required attention measures were used to examine the influence on attention. The results show that listening to music while cycling did not affect workload, speed, SMS interaction or attention. Seven different adaptation behaviours were identified when the cyclists dealt with received text messages. One-fourth of the text messages were replied to while cycling. In general, the cyclists manage to integrate SMS interactions with their cycling behaviour. Nevertheless, there were two occasions when basic attention criteria were violated while texting, which motivate further studies.

Objective: To investigate the influence of prior experience with Level 2 automation on additional task performance during manual and Level 2 partially automated driving.

Background: Level 2 automation is now on the market, but its effects on driver behavior remain unclear. Based on previous studies, we could expect an increase in drivers’ engagement in secondary tasks during Level 2 automated driving, but it is yet unknown how drivers will integrate all the ongoing demands in such situations.

Method: Twenty-one drivers (12 without, 9 with Level 2 automation experience) drove on a highway manually and with Level 2 automation (exemplified by Volvo Pilot Assist generation 2; PA2) while performing an additional task. In half of the conditions, the task could be interrupted (self-paced), and in the other half, it could not (system-paced). Drivers’ visual attention, additional task performance, and other compensatory strategies were analyzed.

Results: Driving with PA2 led to decreased scores in the additional task and more visual attention to the dashboard. In the self-paced condition, all drivers looked more to the task and perceived a lower mental demand. The drivers experienced with PA2 used the system and the task more than the novice group and performed more overtakings.

Conclusions: The additional task interfered more with Level 2 automation than with manual driving. The drivers, particularly the automation novice drivers, used some compensatory strategies.

Applications: Automation designers need to consider these potential effects in the development of future automated systems.