Evaluation of emerging intelligent transport systems to improve safety on level crossings : an overview

Safety at railway level crossings (RLX) is one part of a wider picture of safety within the whole transport system. Governments, the rail industry and road organisations have used a variety of countermeasures for many years to improve RLX safety. New types of interventions are required in order to reduce the number of crashes and associated social costs at railway crossings. This paper presents the results of a large research program which aimed to assess the effectiveness of emerging Intelligent Transport Systems (ITS) interventions, both on-road and in-vehicle based, to improve the safety of car drivers at RLXs in Australia. The three most promising technologies selected from the literature review and focus groups were tested in an advanced driving simulator to provide a detailed assessment of their effects on driver behaviour. The three interventions were: (i) in-vehicle visual warning using a GPS/smartphone navigation-like system, (ii) in-vehicle audio warning and; (iii) on-road intervention known as valet system (warning lights on the road surface activated as a train approaches). The effects of these technologies on 57 participants were assessed in a systematic approach focusing on the safety of the intervention, effects on the road traffic around the crossings and driver’s acceptance of the technology. Given that the ITS interventions were likely to provide a benefit by improving the driver’s awareness of the crossing status in low visibility conditions, such conditions were investigated through curves in the track before arriving at the crossing. ITS interventions were also expected to improve driver behaviour at crossings with high traffic (blocking back issue), which were also investigated at active crossings. The key findings are: (i) interventions at passive crossings are likely to provide safety benefits; (ii) the benefits of ITS interventions on driver behaviour at active crossings are limited; (iii) the trialled ITS interventions did not show any issues in terms of driver distraction, driver acceptance or traffic delays; (iv) these interventions are easy to use, do not increase driver workload substantially; (v) participants’ intention to use the technology is high and; (vi) participants saw most value in succinct messages about approaching trains as opposed to knowing the RLX locations or the imminence of a collision with a train.

Potentiation of the early visual response to learned danger signals in adults and adolescents

The reinforcing effects of aversive outcomes on avoidance behaviour are well established. However, their influence on perceptual processes is less well explored, especially during the transition from adolescence to adulthood. Using electroencephalography, we examined whether learning to actively or passively avoid harm can modulate early visual responses in adolescents and adults. The task included two avoidance conditions, active and passive, where two different warning stimuli predicted the imminent, but avoidable, presentation of an aversive tone. To avoid the aversive outcome, participants had to learn to emit an action (active avoidance) for one of the warning stimuli and omit an action for the other (passive avoidance). Both adults and adolescents performed the task with a high degree of accuracy. For both adolescents and adults, increased N170 event-related potential amplitudes were found for both the active and the passive warning stimuli compared with control conditions. Moreover, the potentiation of the N170 to the warning stimuli was stable and long lasting. Developmental differences were also observed; adolescents showed greater potentiation of the N170 component to danger signals. These findings demonstrate, for the first time, that learned danger signals in an instrumental avoidance task can influence early visual sensory processes in both adults and adolescents.

An Intelligent Driver Warning System

This chapter is focussed on the research and development of an intelligent driver warning system (IDWS) as a means to improve road safety and driving comfort. Two independent IDWS case studies are presented. The first study examines the methodology and implementation for attentive visual tracking and trajectory estimation for dynamic scene segmentation problems. In the second case study, the concept of driver modelling is evaluated which can be used to provide useful feedback to drivers. In both case studies, the quality of IDWS is largely determined by the modelling capability for estimating multiple vehicle trajectories and modelling driving behaviour. A class of modelling techniques based on neural-fuzzy systems, which exhibits provable learning and modelling capability, is proposed. For complex modelling problems where the curse of dimensionality becomes an issue, a network construction algorithm based on Adaptive Spline Modelling of Observation Data (ASMOD) is also proposed.

Warning constraint limit experience

'Warning constraint limit experience' is an installation comprising drawings, a large scale fabric work, and a performative video. This work explores the performative act of drawing and the limits of language and subjectivity. The fabric work acts as a bodily extension that both facilitates and constrains movement during the drawing process and operates as a provisional structure for viewing the work in the gallery. This work was developed and presented at The Lock-Up Cultural Centre, Newcastle NSW in 2011 and revised for the solo exhibition ‘I build my dwelling’, held at Metro Arts in 2012.