Road accidents are a major source of trauma worldwide. Over 1.3 million people are killed in road accidents annually, and collisions are a leading cause of death and injury across all age groups. Aside from the human cost of road accidents, there is a significant financial toll. The US Centre for Disease Control and Prevention estimates that road trauma costs the world economy nearly $2 trillion annually.
According to Richard B. Watson and Peter J. Ryan in their paper, ‘Geospatial Factors Applied to Road Accidents: A Review’, the high number of global road accidents is caused by the increasing numbers of vehicles and drivers on roads, the expansion of road infrastructure due to population growth, and urban encroachment into rural areas.
Analysing these spatial factors, such as the built infrastructure, natural environment features, traffic volume, and road design, can help us better understand the role they play in the severity and frequency of road accidents. This gives policy makers, urban planners, and city managers the knowledge to reduce and, in some cases, even prevent, traffic accidents. To test how effective geospatial analysis can be when applied to road accidents, Watson and Ryan reviewed case studies that used geospatial analysis and visualisation techniques to determine the cause of road accidents in cities worldwide.
Looking at studies in Portugal, the Netherlands, China, the USA, Qatar, and India, Watson and Ryan found a correlation in each study between population density, built-up urban areas, and a higher frequency of road accidents.
Researchers in Lisbon were able to use geospatial analysis to identify streets with the highest number of crashes and the locations of accident hotspots. In the Netherlands, geospatial analysis revealed an association between low socioeconomic areas and higher rates of road accidents. Meanwhile, studies in Detroit and Doha highlighted a correlation between built-up environments and road accidents. In both cities, areas with commercial land use and four-way intersections were found to generally indicate a higher crash rate.
To further test the efficacy of geospatial analysis and visualisation techniques in highlighting the factors that contribute to road accidents, Watson and Ryan implemented their own study in Geelong, Victoria.
Geelong, as a medium-sized city with a well-defined CBD, was chosen due to its similarity with the cities Watson and Ryan examined in their review. With help from students at the Swinburne University of Technology in Melbourne and using data from AURIN, the researchers applied geospatial analysis to Geelong road accidents. Once again, geospatial analysis revealed that more crashes occurred in built-up areas. Hotspots were also identified in this study, with one particularly significant hotspot at Geelong’s GPO. This further reinforces the correlation between built environments and road accidents and demonstrates the potential for geospatial analysis in identifying the cause and number of road crashes.
The implications of this knowledge are significant, particularly for developing countries where accident and fatality rates tend to be much higher. Though developed nations have more cars per head of population, the death rate from road accidents is far higher in less developed nations. Geospatial analysis offers a way for policymakers and urban planners to understand the factors that influence road crashes and fatalities and thus is an important and emerging tool for managing the global problem of road accidents.
However, geospatial analysis relies on data sources for information. AURIN, as an open-source platform, is an integral data source for analysts, providing abundant geospatial and demographic environmental data that is crucial for accurate and transformative research. AURIN is delighted to have supplied such data to this review and thus help to shape research, understanding, and policy, around the growing issue of road safety.
