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Le projet DETER (Detection, Enfoncement & Tutoring for Error Reduction, DRIVE Il V2009) a pour objet le développement et le test de prototypes intégrés d’évaluation et de contrôle de la dégradation des performances du conducteur. Les études réalisées sur simulateur et en situation réelle de conduite ont pour but l’analyse des effets comportementaux, de la fiabilité et de la validition du prototype. D’autres études sont menées afin d’évaluer l’acceptation du système par les usagers ainsi que la portée des procédures administratives « légales ». Dans cette contribution, nous insisterons sur l’importance du sous-système de contrôle de la dégradation de la performance du conducteur. Il s’agit d’un module qui contrôle la capacité du conducteur (conduite en sécurité) via un certain nombre limité de mesures de performance de la conduite. The DETER (Detection, Enforcement & Tutoring for Error Reduction, DRIVE IIV2009) project is concerned with the development and testing of prototypes of onsite, in-vehicle and integrated monitoring, tutoring and enforcement Systems. On the one hand, the project aims to accomplish this goal by carrying out simulator and field studies of in-vehicle and integrated monitoring, tutoring and enforcement systems to assess reliability, validity and behavioural effects. On the other hand, field studies are carried out to assess user acceptance, legal-administrative scope and limitations of on-site tutoring and enforcement systems within the framework of the project implementation. In this contribution the emphasis will be on the driver impairment monitoring subsystem which continuously monitors driver ability to drive safely by a limited number of driving performance measures.

Auditory feedback produced by driver assistance systems can benefit safety. However, auditory feedback is often regarded as annoying, which may result in disuse of the system. An auditory headway feedback system was designed with the aim to improve user acceptance and driving safety. The algorithm used a graded approach, which means that it delivered a more urgent warning if the time headway was smaller. In an on-road test, we compared this design with a conventional binary headway warning system. Participants drove a test vehicle on the highway, once with our graded feedback and once with conventional feedback. User acceptance was assessed through a questionnaire and interview. An inspection of the time headway distributions suggested that participants responded to the auditory feedback for both systems. There were substantial individual differences in time headway, and extremely short headways were rare. These findings suggest that long-term naturalistic trials are needed to assess the safety-effectiveness of graded auditory feedback.

Contains fulltext : 54619.pdf (Publisher’s version ) (Closed access) In user-product interaction the way perception influences accuracy of movement or human error is important. Studies on visual illusions have shown that multi-interpretable images often lead to confusion or error. In the present study we investigated whether multiple-interpretable auditory sequences have a similar effect on motor behavior. An auditory model accounting for the perceptual stability of tone sequences is proposed. On the basis of this model tone sequences were generated that contained multiple levels of perceptual stability. Analogous to a multi-interpretable Necker cube, only one representation of the tone sequences was presumed to be dominant at a specific moment in time. In a perceptual study, the predicted saliency of the perceptual representations was verified. The proposed model predicted the results adequately. While listening to the sequences in a second experiment, participants tapped on a table such that their tapping height reflected the low, middle, and high pitches that they perceived. We found that the variability of the tapping movements was higher for the unstable than for the stable percepts. Collectively, the results of the present study shows that predicting the perceptual stability of auditory sequences is important to gain insights into the relationship between acoustic dimensions and performance accuracy.

Older people may be advised to switch from manual to automatic gear shifting, because they may have difficulties with dividing their attention between gear shifting and other driving tasks such as perceiving other traffic participants. The question is whether older drivers show a better driving performance when using automatic gear shifting instead of manual gear shifting. Twenty young and twenty older drivers participated in a driving simulator study. Each participant drove both in the manual and the automatic gear conditions. Young drivers reported significantly higher risk taking behaviour in traffic than the older drivers. The older drivers experienced more collisions in the driving simulator than the young participants, but this was only true in the manual gear condition. Older participants swerved more than young participants in both gear conditions. Altogether, the driving performance of the older drivers was better in the automatic gear condition compared with the manual gear condition. This research supports the advice for older drivers to use automatic gear shifting.

Introduction Still too many deaths and injuries are a result of road safety limitations within Europe. Road safety measures aimed to change the road environment to reduce the risks on driver errors and to reduce the seriousness of the effects of driver errors are expected to increase road safety. A suitable combination of new technologies with existing infrastructure, or with limited improvements of it, may lead to much more cost-effective solutions (Brookhuis et al. 2006). The In-Safety project was aimed at determining which safety measures are expected to be most effective and in the project also evaluations were performed in pilot sites and modeling laboratories. Methods The methodological approach for the selection and prioritization of the initial set of safety measures is presented and discussed, based on an accident analysis. First, the general approach is described, then the method is presented including the definition of a scenario, how accident statistics are used as a starting point, the generation of safety measures, and the method of selection of safety measures. Finally, the AHP multicriteria analysis method, involved in the final prioritisation of the selected safety measures is presented briefly. Results and conclusion The methodology proves to be appropriate for generating and evaluating self explaining road environment measures and forgiving measures, but safety measures in the urban environment were underrepresented, due to stakeholders’ preferences.

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A variety of Advanced Driver Assistance Systems (ADAS) has been and is still being developed, aiming to make car driving more comfortable and safe, while at the same time enhancing traffic efficiency. However, the successful implementation of ADAS is affected by a variety of technical and non-technical issues, one of them being possible implications in the field of legal liability. Potential liability of system developers and car manufacturers is often labelled as a barrier for the rapid deployment of new technology. In the present contribution the European Product Liability Directive’s concept of a defective product is described and analysed from both a legal and a human factors perspective. In legal debates concerning product liability, generally two different approaches can be distinguished, one which is based on consumer expectations and a second which focuses, rather, on a risk-benefit analysis. As will be explained, the two may be seen as complementary and not as being mutually exclusive.Both tests can only be properly applied with the help of human factor expertise., European Journal of Transport and Infrastructure Research, Vol 5 Nr 4 (2005)

The aim of HASTE is to develop methodologies and guidelines for the assessment of In-Vehicle Information Systems (IVIS). The intention is to devise an assessment regime that is independent of the design of an IVIS and that is based on an evaluation of driving performance while using the system as compared with driving performance when not using the system (baseline driving). The ambition is to provide an assessment regime which: • Is technology-independent; • Has safety-related criteria; • Is cost effective; • Is appropriate for any system design; and • Is validated through real-world testing. The objective of the experiments in this Workpackage (WP2) was to investigate the impact of IVIS task load on driving performance and safety. To achieve this, two surrogate IVISs (SIVISs) were created, one representing cognitive load and the other visual load. Using these SIVISs, it was possible to vary secondary task load systematically. Separate assessments of the effects on driving of the different types of task load were carried out, with as clean a distinction as possible between visual and cognitive load. The objective was also to identify the advantages and disadvantages of the different assessment methods (laboratory, simulator, field), and finally to identify which road types and scenarios are the most productive for testing IVIS. Different groups of drivers were used and scenarios varied in accordance with the protocol and procedure for safety assessment of IVIS as outlined in Deliverable 1 (Roskam et al., 2002). A very large set of experiments was conducted. But in one sense this was one very large multi-national unified and integrated experiment with a common goal, a common experimental protocol and common indicators. The effect of IVIS use in three distinct road categories — urban, rural, and motorway — was investigated. To do this, a total of 14 separate driving simulator experiments were conducted, with each participant experiencing only one type of S-IVIS. All seven driving simulators were used to investigate driving with both S-IVISs on a common rural road. For the most part, each simulator road type had three levels of difficultly with the most difficult being driving when some critical event was triggered (the motorway had only two levels of difficulty: without and with events).

The aim of HASTE is to develop methodologies and guidelines for the assessment of In-Vehicle Information Systems (IVIS). The intention is to devise an assessment regime that is independent of the design of an IVIS and that is based on an evaluation of driving performance while using the system as compared with driving performance when not using the system (baseline driving). The ambition is to provide an assessment regime which: • Is technology-independent; • Has safety-related criteria; • Is cost effective; • Is appropriate for any system design; and • Is validated through real-world testing. The objective of the experiments in this Workpackage (WP2) was to investigate the impact of IVIS task load on driving performance and safety. To achieve this, two surrogate IVISs (SIVISs) were created, one representing cognitive load and the other visual load. Using these SIVISs, it was possible to vary secondary task load systematically. Separate assessments of the effects on driving of the different types of task load were carried out, with as clean a distinction as possible between visual and cognitive load. The objective was also to identify the advantages and disadvantages of the different assessment methods (laboratory, simulator, field), and finally to identify which road types and scenarios are the most productive for testing IVIS. Different groups of drivers were used and scenarios varied in accordance with the protocol and procedure for safety assessment of IVIS as outlined in Deliverable 1 (Roskam et al., 2002). A very large set of experiments was conducted. But in one sense this was one very large multi-national unified and integrated experiment with a common goal, a common experimental protocol and common indicators. The effect of IVIS use in three distinct road categories — urban, rural, and motorway — was investigated. To do this, a total of 14 separate driving simulator experiments were conducted, with each participant experiencing only one type of S-IVIS. All seven driving simulators were used to investigate driving with both S-IVISs on a common rural road. For the most part, each simulator road type had three levels of difficultly with the most difficult being driving when some critical event was triggered (the motorway had only two levels of difficulty: without and with events). For the field (real road) studies, both types of S-IVIS were included in the drives for each participant, with the order of S-IVIS tasks counterbalanced. This was because, for these studies, there was no issue with the drivers learning what might happen in the critical events, since none were staged — all the driving was done in natural settings. The three field studies used different combinations of the road types and all roadway types were completed in a single session. The overall number of experiments, both simulator and field, was 17. A total of 527 participants were used. A large number of indicators of driving performance, particularly related to longitudinal and lateral control, were collected. Also collected was information on secondary task performance (acting as the Surrogate IVIS), both static (not driving) and dynamic (whilst driving). The indicators can be classified into: • Self-reported driving performance • Lateral control • Longitudinal control, i.e. control of speed and distance to a lead vehicle • Workload, such as physiological measures and gaze behaviour • Expert observations of driving performance Following the anaysis of this data, a meta-analysis was carried out to compare the various studies and to identify the most effective indicators. This meta-analysis was intended to single out the most powerful scenarios and to assist in showing which indicators could be dispensed with in subsequent work testing the methods in evaluating some real IVISs. The major dimensions of the study, to some extent in order of importance, were: • IVIS type, visual versus cognitive o Within IVIS type, IVIS level o Within IVIS type, Static IVIS performance versus Dynamic IVIS performance • Simulator and Laboratory studies versus Field Studies o Simulator/Laboratory type • Road category (urban, rural, motorway) o Within Road category, Road level • “Average” drivers versus Elderly drivers • UK drivers versus Portuguese drivers Findings across these dimensions were: S-IVIS Type: The two types of S-IVIS had quite different effects on driving performance. The visual task had pronounced effects in terms of steering and lateral behaviour. On the other hand, the cognitive task caused reduced lateral deviation; in other words it “improved” steering behaviour, though there was also a tendency for drivers to compensate for the task load by shifting away from the road edge. This “improvement” in steering behaviour was accompanied by an increase in glances focussed on the road ahead, at the expense of the periphery. There were indications in some of the results that the predominant negative effect of the cognitive task on driving performance was on longitudinal control in car following. S-IVIS level: Drivers were not always able to manage the trade-off between primary and secondary task, and there were many indications of driving performance being poorest when the secondary task demand was the highest. The elderly drivers were particularly poor at this task management. Static S-IVIS Performance vs Dynamic Performance: Generally, the studies found that there was an interaction between S-IVIS performance across the baseline (static) and three levels of dynamic situation (i.e. the three levels of road difficulty). This advocates the HASTE approach of requiring the driving context to be considered in assessing an IVIS. Static performance did not reliably predict dynamic performance. Simulator vs. Field: The field studies tended to pick up somewhat different effects of the systems than the simulator studies. Additionally, it has not proved possible to test elderly drivers with the visual task due to simulator sickness. This shows the value of the field tests, but also suggests that the incorporation of some additional scenarios or tests in the simulator roads should be considered. These could perhaps take the form of detecting objects in the periphery or detecting changes in the peripheral scene. Simulator Type: The broad conclusion is that the type of simulator or laboratory used in the assessment did not have an effect. Road Category: In the simulator studies, the rural road was the most diagnostic and the motorway the least diagnostic, i.e. the effect sizes from the rural road were generally larger. The urban road did not pick up any additional information that was not provided by the rural road. This means that, for simulator and laboratory assessments, the rural road can be used as the sole road category in the later work of HASTE assessing real IVIS systems as well as in the final HASTE test procedure. In the field studies with the cognitive task, the motorway produced the only indicator with a consistent effect. Road Level: Road level is an important factor. It will be sensible in the later work of the project to consider dispensing with the easiest level of the road. “Average” vs Elderly Drivers: The findings have confirmed the hypothesis proposed in Deliverable 1 (Roskam et al., 2002), that there would be severe problems for elderly drivers in using IVIS while driving, particularly at higher levels of task demand. UK vs Portugal: The controlled comparison of the British and Portuguese showed the expected effect: the Portuguese drivers exhibited riskier driving behaviours. But, reassuringly, the analysis revealed there was no interaction effect of the “country” factor. In other words, results obtained with Portuguese drivers should be as reliable as those obtained with drivers from northern Europe. As regards methodology, the results obtained form this very large set of studies confirm some of the initial decisions made in formulating the HASTE approach. There was clear value to the focus on dynamic evaluation, i.e. of looking at interaction with an IVIS while driving and of identifying the effects of that interaction on driving. Static testing cannot predict how an IVIS will affect steering behaviour or interaction with other road users. The different road levels proved their worth, particularly levels 2 and 3 of the rural road. There is also clear value to the inclusion of events (road level 3), but there is also some scope for improving the events so that the drivers are less able to adapt to their occurrence, by for example slowing down as the lead vehicle comes closer to them. There may also be scope for the inclusion of peripheral detection tasks (PDTs) in the driving task, in order to gain a better understanding of drivers’ ability to assimilate information in the periphery, which is crucial to safety. The results also confirm the value of using a very large number of indicators. Some of these indicators have turned out to be non-diagnostic and therefore can be abandoned in the next phase of the project. Others have turned out to be superfluous in that what they reveal overlaps with the diagnosis provided by other indicators. The meta-analysis has helped to sift through the indicators and test environments to identify the most powerful ones. Important conclusions from the studies are: The effect of the S-IVIS visual task on driving is very clear: increased distraction leads to problems in lateral control. • The effect of the S-IVIS cognitive task is more complex, in that some driving parameters, particularly related to steering control and lateral position appear to improve. However, this improvement seems to be an artefact of greater concentration on the road straight ahead at the expense of information acquired from the periphery. Thought needs to be given to tasks or tests that might capture this loss of information acquisition from the periphery. • Motorway driving in the various simulators and the laboratory was generally less diagnostic, than driving on other road types. • Elderly drivers exhibited very risky driving while performing IVIS tasks • The field studies provided some information that was not provided by the simulator assessments. The subsequent work in the project should consider simulator tasks that can provide analogous information.