An Ontological Approach to Inform HMI Designs for Minimizing Driver Distractions with ADAS

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and efficiency as well as comfort for drivers in the driving process. Recent studies have noticed that when Human Machine Interface (HMI) is not designed properly, an ADAS can cause distraction which would affect its usage and even lead to safety issues. Current understanding of these issues is limited to the context-dependent nature of such systems. This paper reports the development of a holistic conceptualisation of how drivers interact with ADAS and how such interaction could lead to potential distraction. This is done taking an ontological approach to contextualise the potential distraction, driving tasks and user interactions centred on the use of ADAS. Example scenarios are also given to demonstrate how the developed ontology can be used to deduce rules for identifying distraction from ADAS and informing future designs

Compensatory driving behaviour of older drivers with Parkinson's disease. Is it sufficient to counterbalance their driving difficulties?

Drivers with Parkinson’s disease (PD) may have difficulties in their driving competence and these deficits may"br" lead to reduced driver performance and increased accident probability. The objective of the present paper is the"br" analysis of traffic and safety behaviour of drivers with PD and the identification of possible compensatory"br" strategies that these drivers follow, by applying a large driving simulator experiment. A thorough neurological and"br" neuropsychological assessment was carried out and then a driving simulator experiment was applied. 54 elderly"br" drivers of similar demographics went through the whole experimental procedure: 34 healthy controls and 20 PD"br" patients. The following driving performance measures were examined: mean speed, time headway, lateral position,"br" steering angle variability, reaction time, and accident probability, by Generalized Linear Models. Summarizing"br" patients with PD are aware of their driving difficulties and they try to develop - not in a successful way - a"br" compensatory driving behaviour and follow a more conservative driving pattern

Self-assessment of older drivers with brain pathologies: reported habits and self-regulation of driving

The objective of this paper is to analyze the self-reported driving behaviour of older drivers with and without brain pathologies affecting cognition, in order to explore possible differences in self-perception of driving behaviour, through an extensive questionnaire assessment. The diagnostic categories examined include Alzheimer׳s disease, Parkinson׳s disease, and Mild Cognitive Impairment. The questionnaire was answered by 137 drivers with similar demographic characteristics, out of which 44 were healthy individuals and 93 had a brain pathology. It included questions about their driving routines, possible avoidance of driving, and their emotions and behaviours while driving. The participants were also asked about their opinion about in-vehicle driver distraction and how they deal with it. A comparison of the two groups with Kruskal-Wallis and One-Way ANOVAs, produced several statistically significant results. Patients tended to report that they were more likely to avoid using their vehicle because they were afraid of their driving abilities than healthy drivers. Regarding distraction, patients considered it too dangerous to converse with a passenger and even more so, to use the mobile phone and for that reason they reported avoiding to do so. Patients with brain pathologies reported being quite calm while driving. Overall, drivers with brain pathologies were aware of deterioration in their driving performance, and reported trying to compensate for their driving difficulties either by conservative driving or by driving avoidance. © 2016 Elsevier Lt

Comparative assessment of the behaviour of drivers with Mild Cognitive Impairment or Alzheimer's disease in different road and traffic conditions

The objective of this research was the analysis of the driving performance of drivers with Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD), in different road and traffic conditions, on the basis of a driving simulator experiment. In this experiment, healthy “control” drivers, patients with MCI, and patients with AD, drove at several scenarios at the simulator, after a thorough neurological and neuropsychological assessment. The scenarios include driving in rural and urban areas in low and high traffic volumes. The driving performance of healthy and impaired drivers was analysed and compared by means of Repeated Measures General Linear Modelling techniques. A sample of 75 participants was analysed, out of which 23 were MCI patients and 14 were AD patients. Various driving performance measures were examined, including longitudinal and lateral control measures. The results suggest that the two examined cerebral diseases do affect driving performance, and there were common driving patterns for both cerebral diseases, as well as particular characteristics of specific pathologies. More specifically, cognitively impaired drivers drive at lower speeds and with larger headway compared to healthy drivers. Moreover, they appear to have difficulties in positioning the vehicle on the lane. The group of patients had difficulties in all road and traffic environments, and especially when traffic volume was high. Most importantly, both cerebral diseases appear to significantly impair reaction times at incidents. The results of this research suggest that compensatory behaviours developed by impaired drivers are not adequate to counterbalance the direct effects of these cerebral diseases on driving skills. They also demonstrate that driving impairments increase as cognitive impairments become more severe (from MCI to AD). © 2017 Elsevier Lt