Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX

Gaining Situation Awareness Through A Vibrotactile Display To Mitigate Motion Sickness In Fully-Automated Driving Cars

Many previous studies mention that passive drivers or passengers of fullyautomated driving cars have less awareness of the surrounding and more experience to motion sickness symptoms when engaging in non-driving tasks. This occurrence is especially magnified when riding in an urban area with lots of junctions and corners. The aim of the current study is to investigate the effects of peripheral information about upcoming manoeuvres through a vibrotactile display in increasing the fully-automated driving car passengers’ awareness of situations and mitigating their motion sickness level. Twenty participants took part in the experiment which used a Wizard of Oz method to simulate autonomous driving, and the experiment was conducted in an instrumented car on a real road environment. Objective and subjective measurements were gathered. The results show that the implementation of the vibrotactile display increased situation awareness but failed to reduce the motion sickness. This study concludes that in order to mitigate motion sickness inside a fully-automated driving car, more specific information need to be included in the peripheral information. In addition, a device that can actively help in controlling the posture movements should also be implemented in the vehicle

Quantifying Cognitive Efficiency of Display in Human-Machine Systems

As a side effect of fast growing informational technology, information overload becomes prevalent in the operation of many human-machine systems. Overwhelming information can degrade operational performance because it imposes large mental workload on human operators. One way to address this issue is to improve the cognitive efficiency of display. A cognitively efficient display should be more informative while demanding less mental resources so that an operator can process larger displayed information using their limited working memory and achieve better performance. In order to quantitatively evaluate this display property, a Cognitive Efficiency (CE) metric is formulated as the ratio of the measures of two dimensions: display informativeness and required mental resources (each dimension can be affected by display, human, and contextual factors). The first segment of the dissertation discusses the available measurement techniques to construct the CE metric and initially validates the CE metric with basic discrete displays. The second segment demonstrates that displays showing higher cognitive efficiency improve multitask performance. This part also identifies the version of the CE metric that is the most predictive of multitask performance. The last segment of the dissertation applies the CE metric in driving scenarios to evaluate novel speedometer displays; however, it finds that the most efficient display may not better enhance concurrent tracking performance in driving. Although the findings of dissertation show several limitations, they provide valuable insight into the complicated relationship among display, human cognition, and multitask performance in human-machine systems

Musical Haptics

Haptic Musical Instruments; Haptic Psychophysics; Interface Design and Evaluation; User Experience; Musical Performanc