Although cruise control (CC) is available for most cars, no studies have been found which examine how this automation system influences driving behaviour. However, a relatively large number of studies have examined adaptive cruise control (ACC) which compared to CC includes also a distance control. Besides positive effects with regard to a better compliance to speed limits, there are also indications of smaller distances to lead vehicles and slower responses in situations that require immediate braking. Similar effects can be expected for CC as this system takes over longitudinal control as well. To test this hypothesis, a simulator study was conducted at the German Aerospace Center. Twenty-two participants drove different routes (highway and motorway) under three different conditions (assisted by ACC, CC and manual driving without any system). Different driving scenarios were examined including a secondary task condition. On the one hand, both systems lead to lower maximum velocities and less speed limit violations. There was no indication that drivers shift more of their attention towards secondary tasks when driving with CC or ACC. However, there were delayed driver reactions in critical situations, e.g., in a narrow curve or a fog bank. These results give rise to some caution regarding the safety effects of these systems, especially if in the future their range of functionality (e.g., ACC Stop-and-Go) is further increased.
The strong prevalence of human error as a crash causation factor in motorcycle accidents calls for countermeasures that help tackling this issue. Advanced rider assistance systems pursue this goal, providing the riders with support and thus contributing to the prevention of crashes. However, the systems can only enhance riding safety if the riders use them. For this reason, acceptance is a decisive aspect to be considered in the development process of such systems. In order to be able to improve behavioural acceptance, the factors that influence the intention to use the system need to be identified. This paper examines the particularities of motorcycle riding and the characteristics of this user group that should be considered when predicting the acceptance of advanced rider assistance systems. Founded on theories predicting behavioural intention, the acceptance of technologies and the acceptance of driver support systems, a model on the acceptance of advanced rider assistance systems is proposed, including the perceived safety when riding without support, the interface design and the social norm as determinants of the usage intention. Since actual usage cannot be measured in the development stage of the systems, the willingness to have the system installed on the own motorcycle and the willingness to pay for the system are analyzed, constituting relevant conditions that allow for actual usage at a later stage. Its validation with the results from user tests on four advanced rider assistance systems allows confirming the social norm and the interface design as powerful predictors of the acceptance of ARAS, while the extent of perceived safety when riding without support did not have any predictive value in the present study.
This article describes the development of techniques to minimize automobile driver distraction when an in-vehicle information systems (IVIS) that requires visual attention is in use. The authors explain the visual occlusion technique that has been developed as a tool for the assessment of the in-vehicle human-machine interface (HMI) of IVIS in terms of visual demands. The authors addressed an unresolved issue in previous standardized experimental protocols - how subjects make use of the occluded intervals and how this might affect the assessments of visual demands. This study protocol assumed that subjects would continue task performance during occluded periods, leading to an underestimation of visual demands by the occlusion parameters "total shutter open time" (TSOT) and the "occlusion index". The authors predicted that a simple additional loading task to be performed in parallel could disrupt IVIS task performance during the occluded period leading to higher estimations of visual demands by TSOT and R. Their prediction was confirmed by the study findings. The results also showed that under the condition of additional auditory tracking, TSOT and R discriminated more clearly between an "easy" and a "difficult" IVIS task than under the standard condition. They conclude with a discussion of the implications of this research for designers of assessment tools for driver visual distractions.
Am 01.03.2004 wurde auf europäischer Ebene das Expertennetzwerk HUMANIST (HUMAN centred design for Information Society Technologies) eingerichtet, das sich mit Fragen der Implementierung, Gestaltung und Evaluation von Fahrerassistenz- und -informationssystemen aus einer sicherheits- und nutzerorientierten Perspektive befasst. Insgesamt sind 26 Partnerorganisationen aus 15 europäischen Ländern beteiligt. Nach bisher zwei Jahren Laufzeit kann das Netzwerk eine Vielzahl von erfolgreich durchgeführten Veranstaltungen vorweisen (verschiedene werden im Einzelnen aufgeführt). Darüber hinaus wurde ein Post-Graduierten- beziehungsweise ein Post-Doc-Programm ins Leben gerufen. Eine weitere wichtige Initiative bestand in der Beschaffung von Grundlagen für eine gemeinsame Nutzung der bei den beteiligten Partnern vorhandenen Forschungs-Infrastruktur und einer gemeinsam genutzten Datenbasis und virtuellen Arbeitsumgebung. Weiterhin konnten auch wissenschaftliche Ergebnisse erarbeitet werden, die in einigen wesentlichen Ausschnitten dargestellt werden. Dabei handelt es sich um folgende Themen: Nutzerbedürfnisse und Potenziale von Fahrerassistenz- und -informationssystemen; Auswirkung der Nutzung von Fahrerassistenz- und -informationssystemen auf das Fahrverhalten und ihre methodische Erfassung; Fahrerausbildung für die Nutzung von Fahrerassistenz- und -informationssystemen. Abschließend wird auf die im Jahr 2006 geplanten Aktivitäten hingewiesen.