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

The psychology of driving automation: A discussion with Professor Don Norman

Introducing automation into automobiles had inevitable consequences for the driver and driving. Systems that automate longitudinal and lateral vehicle control may reduce the workload of the driver. This raises questions of what the driver is able to do with this 'spare' attentional capacity. Research in our laboratory suggests that there is unlikely to be any spare capacity because the attentional resources are not 'fixed'. Rather, the resources are inextricably linked to task demand. This paper presents some of the arguments for considering the psychological aspects of the driver when designing automation into automobiles. The arguments are presented in a conversation format, based on discussions with Professor Don Norman. Extracts from relevant papers to support the arguments are presented

FESTA. D4 Common vision regarding cooperative systems FOTs

The objective of an FOT is to evaluate in-vehicle functions based on Information Communication Technology (ICT) in order to address specific research questions. These research questions can be related to safety, environment, mobility, traffic efficiency, usage, and acceptance. By addressing the research questions, FOTs promise to furnish the major stakeholders (customers, public authorities, OEMs, suppliers, and the scientific community) with valuable information able to improve their policy-making and market strategies. Individuating the most relevant functions and connected hypothesis to successfully address the above-mentioned research questions is one of the major challenges in an FOT. In this deliverable, the process of individuating the vehicle functions to be tested in an FOT and the relevant connected hypotheses will be elucidated. Specifically, the reader will be guided in the process of 1) selecting the vehicle functions to be tested, 2) defining the connected use cases to test these vehicle functions, 3) identifying the research questions related to these use cases, 4) formulating the hypothesis associated to these research questions, and 5) linking these hypothesis to the correspondent performance indicators

Effects of Single versus Multiple Warnings on Driver Performance

Objective: To explore how a single master alarm system affects drivers’ responses when compared to multiple, distinct warnings. Background: Advanced driver warning systems are intended to improve safety, yet inappropriate integration may increase the complexity of driving, especially in high workload situations. This study investigated the effects of auditory alarm scheme, reliability, and collision event-type on driver performance. Method: A 2x2x4 mixed factorial design investigated the impact of two alarm schemes (master vs. individual) and two levels of alarm reliability (high and low) on distracted drivers’ performance across four collision event-types (frontal collision warnings, left and right lane departure warnings, and follow vehicle fast approach). Results: Participants’ reaction times and accuracy rates were significantly affected by the type of collision event and alarm reliability. The use of individual alarms, rather than a single master alarm, did not significantly affect driving performance in terms of reaction time or response accuracy. Conclusion: Even though a master alarm is a relatively uninformative warning, it produced statistically no different reaction times or accuracy results when compared to information-rich auditory icons, some of which were spatially located. In addition, unreliable alarms negatively impacted driver performance, regardless of event type or alarm scheme. Application: These results have important implications for the development and implementation of multiple driver warning systems.This project was sponsored by the Ford Motor Company