Near misses in remote locations: Investigating rail level crossing incidents in the Pilbara

Rail level crossings are designed to promote safety at road–rail interfaces, but also create the opportunity for conflicts between the two modes of transport. Some of these conflicts can occur due to risk taking behaviour and decision-making errors of road users and represent a significant safety risk. Comparatively little is known about causes of risk-taking behaviour specific to remote locations or regions where the road traffic is dominated by long road vehicles with extremely heavy loads, such as mining and resources traffic. The trains operating in these areas may be up to 3.2 km long and can take a very long time to pass through a crossing. In these circumstances, people must adapt to a very different mode of rail level crossing use than in less remote locations. The current approach to improve safety at road–rail intersections in Australia is to upgrade level crossings with a full complement of active and automatic protection, including boom barriers, flashing lights, bells, and advanced warning signals. However, crashes still occur despite the active protection being operational. The Pilbara region of Western Australia is an example of a remote location with intense mining and resources traffic and, with an abundance of rail operations, numerous level crossings. Anecdotal evidence suggests that level crossing strikes and near misses are a particular safety concern in this region. Given the significance of the Pilbara region to Australia’s economy, problems with traffic flow may hinder opportunities for continued growth enabled by increased reliability and automation of service delivery. Determining the causes of collisions at level crossings in this region is the focus of a mixed-methodological investigation, with the aim of providing potential controls that may reduce or mitigate these occurrences. The research approach discussed is centred on a desktop analysis of level crossing incidents reported by mining companies and an observation structure designed to maximise the efficiency of site visits. Preliminary trends in the data emerging from the first phase of the research include the prevalence of heavy vehicles.